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- mendelian_traits_matched_9/AUPRC_by_chrom/all/Borzoi.LogisticRegression.chrom.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/CADD+Borzoi.LogisticRegression.chrom.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/CADD+GPN-MSA.LogisticRegression.chrom.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/CADD.plus.RawScore.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus.LogisticRegression.chrom.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus_Embeddings.minus.inner_product.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus_Embeddings.plus.cosine_distance.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus_Embeddings.plus.euclidean_distance.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus_LLR.minus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus_absLLR.plus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/Enformer.LogisticRegression.chrom.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA.LogisticRegression.chrom.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_Embeddings.minus.inner_product.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_Embeddings.plus.cosine_distance.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_Embeddings.plus.euclidean_distance.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_InnerProduct.minus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_LLR.minus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_absLLR.plus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final.LogisticRegression.chrom.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final_Embeddings.minus.inner_product.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final_Embeddings.plus.euclidean_distance.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final_InnerProduct.minus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final_LLR.minus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final_absLLR.plus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA.LogisticRegression.chrom.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_Embeddings.minus.inner_product.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_Embeddings.plus.cosine_distance.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_Embeddings.plus.euclidean_distance.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_InnerProduct.minus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_LLR.minus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_absLLR.plus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer.LogisticRegression.chrom.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer_Embeddings.minus.inner_product.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer_Embeddings.plus.euclidean_distance.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer_InnerProduct.minus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer_LLR.minus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer_absLLR.plus.score.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/Sei.LogisticRegression.chrom.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/all/Sei.plus.seqclass_max_absdiff.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Borzoi.LogisticRegression.chrom.subset_from_all.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Borzoi_L2_L2.plus.all.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/CADD.LogisticRegression.chrom.subset_from_all.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/CADD.plus.RawScore.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Caduceus.LogisticRegression.chrom.subset_from_all.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Caduceus_Embeddings.minus.inner_product.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Caduceus_Embeddings.plus.euclidean_distance.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Enformer.LogisticRegression.chrom.subset_from_all.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Enformer_L2_L2.plus.all.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/GPN-MSA.LogisticRegression.chrom.subset_from_all.csv +20 -0
- mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/GPN-MSA_LLR.minus.score.csv +20 -0
mendelian_traits_matched_9/AUPRC_by_chrom/all/Borzoi.LogisticRegression.chrom.csv
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chrom,n,Model,AUPRC
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1,210,Borzoi.LogisticRegression.chrom,0.35585784056971065
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3 |
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2,230,Borzoi.LogisticRegression.chrom,0.36324634212800055
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3,310,Borzoi.LogisticRegression.chrom,0.4949083506109349
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5,20,Borzoi.LogisticRegression.chrom,0.10238095238095238
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6,30,Borzoi.LogisticRegression.chrom,0.8055555555555556
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7,210,Borzoi.LogisticRegression.chrom,0.2288318105491881
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8,70,Borzoi.LogisticRegression.chrom,0.3497267759562841
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9,240,Borzoi.LogisticRegression.chrom,0.4622101629278873
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10,190,Borzoi.LogisticRegression.chrom,0.3624165104924694
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11,480,Borzoi.LogisticRegression.chrom,0.6102857980339427
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12,30,Borzoi.LogisticRegression.chrom,0.7142857142857142
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13,210,Borzoi.LogisticRegression.chrom,0.4811019775032541
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14,40,Borzoi.LogisticRegression.chrom,0.14066176470588235
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16,80,Borzoi.LogisticRegression.chrom,0.8970734126984128
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17,60,Borzoi.LogisticRegression.chrom,0.39125881834215165
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19,400,Borzoi.LogisticRegression.chrom,0.5063787662081095
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20,50,Borzoi.LogisticRegression.chrom,0.7912087912087913
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22,20,Borzoi.LogisticRegression.chrom,1.0
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X,500,Borzoi.LogisticRegression.chrom,0.595317006258727
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mendelian_traits_matched_9/AUPRC_by_chrom/all/CADD+Borzoi.LogisticRegression.chrom.csv
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chrom,n,Model,AUPRC
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1,210,CADD+Borzoi.LogisticRegression.chrom,0.5291321235067817
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3 |
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2,230,CADD+Borzoi.LogisticRegression.chrom,0.8475719458854303
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3,310,CADD+Borzoi.LogisticRegression.chrom,0.8715596707922036
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5,20,CADD+Borzoi.LogisticRegression.chrom,0.75
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6,30,CADD+Borzoi.LogisticRegression.chrom,0.4037037037037037
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7,210,CADD+Borzoi.LogisticRegression.chrom,0.8531952056930068
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8,70,CADD+Borzoi.LogisticRegression.chrom,0.6714320625610948
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9,240,CADD+Borzoi.LogisticRegression.chrom,0.8794443708949461
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10,190,CADD+Borzoi.LogisticRegression.chrom,0.659250034756613
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11,480,CADD+Borzoi.LogisticRegression.chrom,0.6855727717448943
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12,30,CADD+Borzoi.LogisticRegression.chrom,1.0
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13,210,CADD+Borzoi.LogisticRegression.chrom,0.6857860132702304
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14,40,CADD+Borzoi.LogisticRegression.chrom,0.439572192513369
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16,80,CADD+Borzoi.LogisticRegression.chrom,0.9206845238095238
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17,60,CADD+Borzoi.LogisticRegression.chrom,0.5552641802641802
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19,400,CADD+Borzoi.LogisticRegression.chrom,0.8149251979346507
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20,50,CADD+Borzoi.LogisticRegression.chrom,0.837037037037037
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22,20,CADD+Borzoi.LogisticRegression.chrom,1.0
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X,500,CADD+Borzoi.LogisticRegression.chrom,0.7530334420717857
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mendelian_traits_matched_9/AUPRC_by_chrom/all/CADD+GPN-MSA.LogisticRegression.chrom.csv
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chrom,n,Model,AUPRC
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2 |
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1,210,CADD+GPN-MSA.LogisticRegression.chrom,0.6274343999309111
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3 |
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2,230,CADD+GPN-MSA.LogisticRegression.chrom,0.9578432668164396
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3,310,CADD+GPN-MSA.LogisticRegression.chrom,0.8916761864869845
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5,20,CADD+GPN-MSA.LogisticRegression.chrom,0.5833333333333333
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6,30,CADD+GPN-MSA.LogisticRegression.chrom,0.7575757575757576
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7,210,CADD+GPN-MSA.LogisticRegression.chrom,0.9682539682539684
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8,70,CADD+GPN-MSA.LogisticRegression.chrom,0.889848246991104
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9,240,CADD+GPN-MSA.LogisticRegression.chrom,0.9184749899581555
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10,190,CADD+GPN-MSA.LogisticRegression.chrom,0.6097961397733949
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11,480,CADD+GPN-MSA.LogisticRegression.chrom,0.7414873685740329
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12,30,CADD+GPN-MSA.LogisticRegression.chrom,1.0
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13,210,CADD+GPN-MSA.LogisticRegression.chrom,0.7835773040215014
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14,40,CADD+GPN-MSA.LogisticRegression.chrom,0.4866600790513834
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16,80,CADD+GPN-MSA.LogisticRegression.chrom,0.8152597402597402
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17,60,CADD+GPN-MSA.LogisticRegression.chrom,0.8999999999999999
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19,400,CADD+GPN-MSA.LogisticRegression.chrom,0.9737139485434267
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20,50,CADD+GPN-MSA.LogisticRegression.chrom,1.0
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22,20,CADD+GPN-MSA.LogisticRegression.chrom,1.0
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X,500,CADD+GPN-MSA.LogisticRegression.chrom,0.8904969178852727
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mendelian_traits_matched_9/AUPRC_by_chrom/all/CADD.plus.RawScore.csv
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chrom,n,Model,AUPRC
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1,210,CADD.plus.RawScore,0.4129625555342457
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2,230,CADD.plus.RawScore,0.8002570388128496
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3,310,CADD.plus.RawScore,0.8429503303714627
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5,20,CADD.plus.RawScore,0.3088235294117647
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6,30,CADD.plus.RawScore,0.2415966386554622
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7,210,CADD.plus.RawScore,0.8950129988271784
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8,70,CADD.plus.RawScore,0.4716484006626736
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+
9,240,CADD.plus.RawScore,0.7128260796937943
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+
10,190,CADD.plus.RawScore,0.5615519097400601
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+
11,480,CADD.plus.RawScore,0.6463323901077855
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12,30,CADD.plus.RawScore,1.0
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13,210,CADD.plus.RawScore,0.6384040987280705
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14,40,CADD.plus.RawScore,0.13773148148148145
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+
16,80,CADD.plus.RawScore,0.6744306418219461
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17,60,CADD.plus.RawScore,0.745054945054945
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19,400,CADD.plus.RawScore,0.8961158962372263
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20,50,CADD.plus.RawScore,0.8232558139534885
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22,20,CADD.plus.RawScore,1.0
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X,500,CADD.plus.RawScore,0.7296850544024586
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mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus.LogisticRegression.chrom.csv
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chrom,n,Model,AUPRC
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1,210,Caduceus.LogisticRegression.chrom,0.11152550820129042
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2,230,Caduceus.LogisticRegression.chrom,0.10474624254944398
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3,310,Caduceus.LogisticRegression.chrom,0.6503160205649838
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5,20,Caduceus.LogisticRegression.chrom,0.11437908496732026
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6,30,Caduceus.LogisticRegression.chrom,0.14825174825174825
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7,210,Caduceus.LogisticRegression.chrom,0.802118130568114
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8,70,Caduceus.LogisticRegression.chrom,0.3027727174785998
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9,240,Caduceus.LogisticRegression.chrom,0.09203504122316915
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10,190,Caduceus.LogisticRegression.chrom,0.25332122414732383
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11,480,Caduceus.LogisticRegression.chrom,0.0720856789417794
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12,30,Caduceus.LogisticRegression.chrom,0.2148148148148148
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13,210,Caduceus.LogisticRegression.chrom,0.36091057264776577
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14,40,Caduceus.LogisticRegression.chrom,0.5629117259552042
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16,80,Caduceus.LogisticRegression.chrom,0.2039423509520492
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17,60,Caduceus.LogisticRegression.chrom,0.19185120435120434
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19,400,Caduceus.LogisticRegression.chrom,0.14060765335796077
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+
20,50,Caduceus.LogisticRegression.chrom,0.2859663865546218
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+
22,20,Caduceus.LogisticRegression.chrom,0.09821428571428571
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+
X,500,Caduceus.LogisticRegression.chrom,0.09254823352244966
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mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus_Embeddings.minus.inner_product.csv
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chrom,n,Model,AUPRC
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1,210,Caduceus_Embeddings.minus.inner_product,0.15135674297515564
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2,230,Caduceus_Embeddings.minus.inner_product,0.1868821054855781
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+
3,310,Caduceus_Embeddings.minus.inner_product,0.12523641541148628
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5,20,Caduceus_Embeddings.minus.inner_product,0.5714285714285714
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+
6,30,Caduceus_Embeddings.minus.inner_product,0.148109243697479
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+
7,210,Caduceus_Embeddings.minus.inner_product,0.1362992099214087
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8,70,Caduceus_Embeddings.minus.inner_product,0.07273278680908898
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+
9,240,Caduceus_Embeddings.minus.inner_product,0.17812601057698604
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+
10,190,Caduceus_Embeddings.minus.inner_product,0.08541813058340143
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11,480,Caduceus_Embeddings.minus.inner_product,0.06924122946357933
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12,30,Caduceus_Embeddings.minus.inner_product,0.7192982456140351
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+
13,210,Caduceus_Embeddings.minus.inner_product,0.12148482624527741
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14,40,Caduceus_Embeddings.minus.inner_product,0.10082877648667121
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16,80,Caduceus_Embeddings.minus.inner_product,0.40122100122100124
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17,60,Caduceus_Embeddings.minus.inner_product,0.12892854991366287
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19,400,Caduceus_Embeddings.minus.inner_product,0.12641330204302254
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20,50,Caduceus_Embeddings.minus.inner_product,0.12513960113960115
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22,20,Caduceus_Embeddings.minus.inner_product,0.08496732026143791
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X,500,Caduceus_Embeddings.minus.inner_product,0.07633369589997713
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mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus_Embeddings.plus.cosine_distance.csv
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chrom,n,Model,AUPRC
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2 |
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1,210,Caduceus_Embeddings.plus.cosine_distance,0.15100467285524194
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3 |
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2,230,Caduceus_Embeddings.plus.cosine_distance,0.21143968894251655
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+
3,310,Caduceus_Embeddings.plus.cosine_distance,0.15055771025759793
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5,20,Caduceus_Embeddings.plus.cosine_distance,0.22916666666666666
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6,30,Caduceus_Embeddings.plus.cosine_distance,0.1619981325863679
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7,210,Caduceus_Embeddings.plus.cosine_distance,0.1515598901263878
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8,70,Caduceus_Embeddings.plus.cosine_distance,0.11546991295883027
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+
9,240,Caduceus_Embeddings.plus.cosine_distance,0.1022792897789821
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10,190,Caduceus_Embeddings.plus.cosine_distance,0.0832503659621521
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11 |
+
11,480,Caduceus_Embeddings.plus.cosine_distance,0.1122279394832056
|
12 |
+
12,30,Caduceus_Embeddings.plus.cosine_distance,0.11341269841269841
|
13 |
+
13,210,Caduceus_Embeddings.plus.cosine_distance,0.07680409699815019
|
14 |
+
14,40,Caduceus_Embeddings.plus.cosine_distance,0.17092505018201615
|
15 |
+
16,80,Caduceus_Embeddings.plus.cosine_distance,0.12876386454551417
|
16 |
+
17,60,Caduceus_Embeddings.plus.cosine_distance,0.20579172289698605
|
17 |
+
19,400,Caduceus_Embeddings.plus.cosine_distance,0.1685012215001852
|
18 |
+
20,50,Caduceus_Embeddings.plus.cosine_distance,0.11131636562671046
|
19 |
+
22,20,Caduceus_Embeddings.plus.cosine_distance,0.31666666666666665
|
20 |
+
X,500,Caduceus_Embeddings.plus.cosine_distance,0.11178035906277
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus_Embeddings.plus.euclidean_distance.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,Caduceus_Embeddings.plus.euclidean_distance,0.15193716459454382
|
3 |
+
2,230,Caduceus_Embeddings.plus.euclidean_distance,0.19847274566657927
|
4 |
+
3,310,Caduceus_Embeddings.plus.euclidean_distance,0.14134354509605732
|
5 |
+
5,20,Caduceus_Embeddings.plus.euclidean_distance,0.22916666666666666
|
6 |
+
6,30,Caduceus_Embeddings.plus.euclidean_distance,0.2013888888888889
|
7 |
+
7,210,Caduceus_Embeddings.plus.euclidean_distance,0.1499366760938221
|
8 |
+
8,70,Caduceus_Embeddings.plus.euclidean_distance,0.13115680615680614
|
9 |
+
9,240,Caduceus_Embeddings.plus.euclidean_distance,0.09809031243284913
|
10 |
+
10,190,Caduceus_Embeddings.plus.euclidean_distance,0.08346281887003036
|
11 |
+
11,480,Caduceus_Embeddings.plus.euclidean_distance,0.11746153917725763
|
12 |
+
12,30,Caduceus_Embeddings.plus.euclidean_distance,0.10507936507936508
|
13 |
+
13,210,Caduceus_Embeddings.plus.euclidean_distance,0.07338270749352274
|
14 |
+
14,40,Caduceus_Embeddings.plus.euclidean_distance,0.18283991228070173
|
15 |
+
16,80,Caduceus_Embeddings.plus.euclidean_distance,0.1244690957190957
|
16 |
+
17,60,Caduceus_Embeddings.plus.euclidean_distance,0.20143987104513422
|
17 |
+
19,400,Caduceus_Embeddings.plus.euclidean_distance,0.16776112056600262
|
18 |
+
20,50,Caduceus_Embeddings.plus.euclidean_distance,0.10919439403105465
|
19 |
+
22,20,Caduceus_Embeddings.plus.euclidean_distance,0.31666666666666665
|
20 |
+
X,500,Caduceus_Embeddings.plus.euclidean_distance,0.12138311809686547
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus_LLR.minus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,Caduceus_LLR.minus.score,0.16396125003849282
|
3 |
+
2,230,Caduceus_LLR.minus.score,0.1026840337066138
|
4 |
+
3,310,Caduceus_LLR.minus.score,0.11633482699404223
|
5 |
+
5,20,Caduceus_LLR.minus.score,0.08125
|
6 |
+
6,30,Caduceus_LLR.minus.score,0.12905982905982905
|
7 |
+
7,210,Caduceus_LLR.minus.score,0.08747307742398475
|
8 |
+
8,70,Caduceus_LLR.minus.score,0.09358312089404527
|
9 |
+
9,240,Caduceus_LLR.minus.score,0.11059618676101962
|
10 |
+
10,190,Caduceus_LLR.minus.score,0.12074548829631646
|
11 |
+
11,480,Caduceus_LLR.minus.score,0.10757622909372277
|
12 |
+
12,30,Caduceus_LLR.minus.score,0.16798941798941797
|
13 |
+
13,210,Caduceus_LLR.minus.score,0.10549766623599263
|
14 |
+
14,40,Caduceus_LLR.minus.score,0.10025833997873472
|
15 |
+
16,80,Caduceus_LLR.minus.score,0.07755296379184398
|
16 |
+
17,60,Caduceus_LLR.minus.score,0.12852461265886134
|
17 |
+
19,400,Caduceus_LLR.minus.score,0.0975821077128583
|
18 |
+
20,50,Caduceus_LLR.minus.score,0.1508545600349931
|
19 |
+
22,20,Caduceus_LLR.minus.score,0.10096153846153846
|
20 |
+
X,500,Caduceus_LLR.minus.score,0.08937647574990194
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/Caduceus_absLLR.plus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,Caduceus_absLLR.plus.score,0.15263720404394523
|
3 |
+
2,230,Caduceus_absLLR.plus.score,0.06371889655383055
|
4 |
+
3,310,Caduceus_absLLR.plus.score,0.08345882660666887
|
5 |
+
5,20,Caduceus_absLLR.plus.score,0.13596491228070173
|
6 |
+
6,30,Caduceus_absLLR.plus.score,0.08267206477732794
|
7 |
+
7,210,Caduceus_absLLR.plus.score,0.08540343866361044
|
8 |
+
8,70,Caduceus_absLLR.plus.score,0.07283836659627724
|
9 |
+
9,240,Caduceus_absLLR.plus.score,0.08577944633238588
|
10 |
+
10,190,Caduceus_absLLR.plus.score,0.0777317620432655
|
11 |
+
11,480,Caduceus_absLLR.plus.score,0.08497544281260411
|
12 |
+
12,30,Caduceus_absLLR.plus.score,0.13611111111111113
|
13 |
+
13,210,Caduceus_absLLR.plus.score,0.07800244127021269
|
14 |
+
14,40,Caduceus_absLLR.plus.score,0.14520123839009286
|
15 |
+
16,80,Caduceus_absLLR.plus.score,0.09395719463162705
|
16 |
+
17,60,Caduceus_absLLR.plus.score,0.15600896393579322
|
17 |
+
19,400,Caduceus_absLLR.plus.score,0.07296065615137605
|
18 |
+
20,50,Caduceus_absLLR.plus.score,0.10638739309471017
|
19 |
+
22,20,Caduceus_absLLR.plus.score,0.08846153846153847
|
20 |
+
X,500,Caduceus_absLLR.plus.score,0.08075800178035818
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/Enformer.LogisticRegression.chrom.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,Enformer.LogisticRegression.chrom,0.295668221077379
|
3 |
+
2,230,Enformer.LogisticRegression.chrom,0.6718695580728805
|
4 |
+
3,310,Enformer.LogisticRegression.chrom,0.33856194049732047
|
5 |
+
5,20,Enformer.LogisticRegression.chrom,0.1125
|
6 |
+
6,30,Enformer.LogisticRegression.chrom,0.5166666666666666
|
7 |
+
7,210,Enformer.LogisticRegression.chrom,0.1923269201185724
|
8 |
+
8,70,Enformer.LogisticRegression.chrom,0.2795049223620652
|
9 |
+
9,240,Enformer.LogisticRegression.chrom,0.5028024000848269
|
10 |
+
10,190,Enformer.LogisticRegression.chrom,0.39868185624801206
|
11 |
+
11,480,Enformer.LogisticRegression.chrom,0.3458051117191732
|
12 |
+
12,30,Enformer.LogisticRegression.chrom,0.7023809523809523
|
13 |
+
13,210,Enformer.LogisticRegression.chrom,0.6554078243520323
|
14 |
+
14,40,Enformer.LogisticRegression.chrom,0.11875
|
15 |
+
16,80,Enformer.LogisticRegression.chrom,0.7322601650378019
|
16 |
+
17,60,Enformer.LogisticRegression.chrom,0.4566679587676228
|
17 |
+
19,400,Enformer.LogisticRegression.chrom,0.3910519692540065
|
18 |
+
20,50,Enformer.LogisticRegression.chrom,0.9666666666666666
|
19 |
+
22,20,Enformer.LogisticRegression.chrom,1.0
|
20 |
+
X,500,Enformer.LogisticRegression.chrom,0.541780653574967
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA.LogisticRegression.chrom.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN-MSA.LogisticRegression.chrom,0.3432037654277196
|
3 |
+
2,230,GPN-MSA.LogisticRegression.chrom,0.9393670511682932
|
4 |
+
3,310,GPN-MSA.LogisticRegression.chrom,0.8616111733221439
|
5 |
+
5,20,GPN-MSA.LogisticRegression.chrom,0.3269230769230769
|
6 |
+
6,30,GPN-MSA.LogisticRegression.chrom,0.8666666666666667
|
7 |
+
7,210,GPN-MSA.LogisticRegression.chrom,0.9339840389865164
|
8 |
+
8,70,GPN-MSA.LogisticRegression.chrom,0.6452415509019283
|
9 |
+
9,240,GPN-MSA.LogisticRegression.chrom,0.9017968261109646
|
10 |
+
10,190,GPN-MSA.LogisticRegression.chrom,0.5080809111651946
|
11 |
+
11,480,GPN-MSA.LogisticRegression.chrom,0.5242451261494039
|
12 |
+
12,30,GPN-MSA.LogisticRegression.chrom,1.0
|
13 |
+
13,210,GPN-MSA.LogisticRegression.chrom,0.5022959513563106
|
14 |
+
14,40,GPN-MSA.LogisticRegression.chrom,0.24486714975845408
|
15 |
+
16,80,GPN-MSA.LogisticRegression.chrom,0.7871355397951143
|
16 |
+
17,60,GPN-MSA.LogisticRegression.chrom,0.7837301587301587
|
17 |
+
19,400,GPN-MSA.LogisticRegression.chrom,0.9401595690048155
|
18 |
+
20,50,GPN-MSA.LogisticRegression.chrom,0.9666666666666666
|
19 |
+
22,20,GPN-MSA.LogisticRegression.chrom,1.0
|
20 |
+
X,500,GPN-MSA.LogisticRegression.chrom,0.4439748737944069
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_Embeddings.minus.inner_product.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN-MSA_Embeddings.minus.inner_product,0.19069579036574189
|
3 |
+
2,230,GPN-MSA_Embeddings.minus.inner_product,0.2614221780164654
|
4 |
+
3,310,GPN-MSA_Embeddings.minus.inner_product,0.18469406558544416
|
5 |
+
5,20,GPN-MSA_Embeddings.minus.inner_product,0.5909090909090909
|
6 |
+
6,30,GPN-MSA_Embeddings.minus.inner_product,0.18055555555555555
|
7 |
+
7,210,GPN-MSA_Embeddings.minus.inner_product,0.5152789610601404
|
8 |
+
8,70,GPN-MSA_Embeddings.minus.inner_product,0.3789042488175065
|
9 |
+
9,240,GPN-MSA_Embeddings.minus.inner_product,0.5261336620948419
|
10 |
+
10,190,GPN-MSA_Embeddings.minus.inner_product,0.16550349152929472
|
11 |
+
11,480,GPN-MSA_Embeddings.minus.inner_product,0.24720094651519992
|
12 |
+
12,30,GPN-MSA_Embeddings.minus.inner_product,0.45833333333333326
|
13 |
+
13,210,GPN-MSA_Embeddings.minus.inner_product,0.23101784849126222
|
14 |
+
14,40,GPN-MSA_Embeddings.minus.inner_product,0.2833333333333333
|
15 |
+
16,80,GPN-MSA_Embeddings.minus.inner_product,0.35197580645161286
|
16 |
+
17,60,GPN-MSA_Embeddings.minus.inner_product,0.44201607267645004
|
17 |
+
19,400,GPN-MSA_Embeddings.minus.inner_product,0.23465582198076043
|
18 |
+
20,50,GPN-MSA_Embeddings.minus.inner_product,0.3574786324786325
|
19 |
+
22,20,GPN-MSA_Embeddings.minus.inner_product,0.41666666666666663
|
20 |
+
X,500,GPN-MSA_Embeddings.minus.inner_product,0.3673765971118938
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_Embeddings.plus.cosine_distance.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
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|
|
|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN-MSA_Embeddings.plus.cosine_distance,0.18710941456843205
|
3 |
+
2,230,GPN-MSA_Embeddings.plus.cosine_distance,0.13879087125640258
|
4 |
+
3,310,GPN-MSA_Embeddings.plus.cosine_distance,0.13807517199524522
|
5 |
+
5,20,GPN-MSA_Embeddings.plus.cosine_distance,0.3333333333333333
|
6 |
+
6,30,GPN-MSA_Embeddings.plus.cosine_distance,0.13141025641025642
|
7 |
+
7,210,GPN-MSA_Embeddings.plus.cosine_distance,0.16680540147691303
|
8 |
+
8,70,GPN-MSA_Embeddings.plus.cosine_distance,0.16716301623624277
|
9 |
+
9,240,GPN-MSA_Embeddings.plus.cosine_distance,0.2774294363079936
|
10 |
+
10,190,GPN-MSA_Embeddings.plus.cosine_distance,0.11596533313754422
|
11 |
+
11,480,GPN-MSA_Embeddings.plus.cosine_distance,0.2524366700353653
|
12 |
+
12,30,GPN-MSA_Embeddings.plus.cosine_distance,0.14027777777777778
|
13 |
+
13,210,GPN-MSA_Embeddings.plus.cosine_distance,0.17676178908810075
|
14 |
+
14,40,GPN-MSA_Embeddings.plus.cosine_distance,0.17045454545454547
|
15 |
+
16,80,GPN-MSA_Embeddings.plus.cosine_distance,0.26891114701469393
|
16 |
+
17,60,GPN-MSA_Embeddings.plus.cosine_distance,0.4309368406408681
|
17 |
+
19,400,GPN-MSA_Embeddings.plus.cosine_distance,0.14620504646359095
|
18 |
+
20,50,GPN-MSA_Embeddings.plus.cosine_distance,0.20722431077694237
|
19 |
+
22,20,GPN-MSA_Embeddings.plus.cosine_distance,0.375
|
20 |
+
X,500,GPN-MSA_Embeddings.plus.cosine_distance,0.30009004639076053
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_Embeddings.plus.euclidean_distance.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN-MSA_Embeddings.plus.euclidean_distance,0.18431302173509773
|
3 |
+
2,230,GPN-MSA_Embeddings.plus.euclidean_distance,0.13737338421191106
|
4 |
+
3,310,GPN-MSA_Embeddings.plus.euclidean_distance,0.13786683704165942
|
5 |
+
5,20,GPN-MSA_Embeddings.plus.euclidean_distance,0.3333333333333333
|
6 |
+
6,30,GPN-MSA_Embeddings.plus.euclidean_distance,0.13141025641025642
|
7 |
+
7,210,GPN-MSA_Embeddings.plus.euclidean_distance,0.16582826886621244
|
8 |
+
8,70,GPN-MSA_Embeddings.plus.euclidean_distance,0.16716301623624277
|
9 |
+
9,240,GPN-MSA_Embeddings.plus.euclidean_distance,0.2757585105689618
|
10 |
+
10,190,GPN-MSA_Embeddings.plus.euclidean_distance,0.11583138476119834
|
11 |
+
11,480,GPN-MSA_Embeddings.plus.euclidean_distance,0.25086581360810045
|
12 |
+
12,30,GPN-MSA_Embeddings.plus.euclidean_distance,0.14027777777777778
|
13 |
+
13,210,GPN-MSA_Embeddings.plus.euclidean_distance,0.1763170274436914
|
14 |
+
14,40,GPN-MSA_Embeddings.plus.euclidean_distance,0.17045454545454547
|
15 |
+
16,80,GPN-MSA_Embeddings.plus.euclidean_distance,0.26891114701469393
|
16 |
+
17,60,GPN-MSA_Embeddings.plus.euclidean_distance,0.4309368406408681
|
17 |
+
19,400,GPN-MSA_Embeddings.plus.euclidean_distance,0.1453244249660683
|
18 |
+
20,50,GPN-MSA_Embeddings.plus.euclidean_distance,0.20511904761904765
|
19 |
+
22,20,GPN-MSA_Embeddings.plus.euclidean_distance,0.375
|
20 |
+
X,500,GPN-MSA_Embeddings.plus.euclidean_distance,0.2986289550000408
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_InnerProduct.minus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
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|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN-MSA_InnerProduct.minus.score,0.19069579036574189
|
3 |
+
2,230,GPN-MSA_InnerProduct.minus.score,0.26128101483182387
|
4 |
+
3,310,GPN-MSA_InnerProduct.minus.score,0.18469406558544416
|
5 |
+
5,20,GPN-MSA_InnerProduct.minus.score,0.5909090909090909
|
6 |
+
6,30,GPN-MSA_InnerProduct.minus.score,0.18055555555555555
|
7 |
+
7,210,GPN-MSA_InnerProduct.minus.score,0.5152789610601404
|
8 |
+
8,70,GPN-MSA_InnerProduct.minus.score,0.3789042488175065
|
9 |
+
9,240,GPN-MSA_InnerProduct.minus.score,0.5261336620948418
|
10 |
+
10,190,GPN-MSA_InnerProduct.minus.score,0.16554923822981393
|
11 |
+
11,480,GPN-MSA_InnerProduct.minus.score,0.24722698188298725
|
12 |
+
12,30,GPN-MSA_InnerProduct.minus.score,0.45833333333333326
|
13 |
+
13,210,GPN-MSA_InnerProduct.minus.score,0.23101784849126222
|
14 |
+
14,40,GPN-MSA_InnerProduct.minus.score,0.2833333333333333
|
15 |
+
16,80,GPN-MSA_InnerProduct.minus.score,0.35197580645161286
|
16 |
+
17,60,GPN-MSA_InnerProduct.minus.score,0.44201607267645004
|
17 |
+
19,400,GPN-MSA_InnerProduct.minus.score,0.23465582198076046
|
18 |
+
20,50,GPN-MSA_InnerProduct.minus.score,0.3574786324786325
|
19 |
+
22,20,GPN-MSA_InnerProduct.minus.score,0.41666666666666663
|
20 |
+
X,500,GPN-MSA_InnerProduct.minus.score,0.3673765971118938
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_LLR.minus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN-MSA_LLR.minus.score,0.4417955223178555
|
3 |
+
2,230,GPN-MSA_LLR.minus.score,0.8905784976501564
|
4 |
+
3,310,GPN-MSA_LLR.minus.score,0.7545502630966198
|
5 |
+
5,20,GPN-MSA_LLR.minus.score,0.34090909090909094
|
6 |
+
6,30,GPN-MSA_LLR.minus.score,0.1865079365079365
|
7 |
+
7,210,GPN-MSA_LLR.minus.score,0.8973596549068968
|
8 |
+
8,70,GPN-MSA_LLR.minus.score,0.715126050420168
|
9 |
+
9,240,GPN-MSA_LLR.minus.score,0.7376088917287991
|
10 |
+
10,190,GPN-MSA_LLR.minus.score,0.3852360888800874
|
11 |
+
11,480,GPN-MSA_LLR.minus.score,0.639175946508193
|
12 |
+
12,30,GPN-MSA_LLR.minus.score,1.0
|
13 |
+
13,210,GPN-MSA_LLR.minus.score,0.6683465217444029
|
14 |
+
14,40,GPN-MSA_LLR.minus.score,0.1853354978354978
|
15 |
+
16,80,GPN-MSA_LLR.minus.score,0.5659447986653869
|
16 |
+
17,60,GPN-MSA_LLR.minus.score,0.7354166666666666
|
17 |
+
19,400,GPN-MSA_LLR.minus.score,0.9090662422517078
|
18 |
+
20,50,GPN-MSA_LLR.minus.score,0.7294117647058824
|
19 |
+
22,20,GPN-MSA_LLR.minus.score,0.7
|
20 |
+
X,500,GPN-MSA_LLR.minus.score,0.6531952615307103
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN-MSA_absLLR.plus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN-MSA_absLLR.plus.score,0.3745467628870028
|
3 |
+
2,230,GPN-MSA_absLLR.plus.score,0.8845856558900036
|
4 |
+
3,310,GPN-MSA_absLLR.plus.score,0.7309895520862926
|
5 |
+
5,20,GPN-MSA_absLLR.plus.score,0.3125
|
6 |
+
6,30,GPN-MSA_absLLR.plus.score,0.12910481331533963
|
7 |
+
7,210,GPN-MSA_absLLR.plus.score,0.8267600077340236
|
8 |
+
8,70,GPN-MSA_absLLR.plus.score,0.6937925170068027
|
9 |
+
9,240,GPN-MSA_absLLR.plus.score,0.6983047473129145
|
10 |
+
10,190,GPN-MSA_absLLR.plus.score,0.3269696276245758
|
11 |
+
11,480,GPN-MSA_absLLR.plus.score,0.5806582074608586
|
12 |
+
12,30,GPN-MSA_absLLR.plus.score,1.0
|
13 |
+
13,210,GPN-MSA_absLLR.plus.score,0.644185230680923
|
14 |
+
14,40,GPN-MSA_absLLR.plus.score,0.14303751803751802
|
15 |
+
16,80,GPN-MSA_absLLR.plus.score,0.5198108622922168
|
16 |
+
17,60,GPN-MSA_absLLR.plus.score,0.7066022544283413
|
17 |
+
19,400,GPN-MSA_absLLR.plus.score,0.8868742457629345
|
18 |
+
20,50,GPN-MSA_absLLR.plus.score,0.49603174603174605
|
19 |
+
22,20,GPN-MSA_absLLR.plus.score,0.6428571428571428
|
20 |
+
X,500,GPN-MSA_absLLR.plus.score,0.6288500191673085
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final.LogisticRegression.chrom.csv
ADDED
@@ -0,0 +1,20 @@
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN_final.LogisticRegression.chrom,0.16251280357505735
|
3 |
+
2,230,GPN_final.LogisticRegression.chrom,0.4628458889834635
|
4 |
+
3,310,GPN_final.LogisticRegression.chrom,0.14393034486362946
|
5 |
+
5,20,GPN_final.LogisticRegression.chrom,0.12142857142857143
|
6 |
+
6,30,GPN_final.LogisticRegression.chrom,0.3333333333333333
|
7 |
+
7,210,GPN_final.LogisticRegression.chrom,0.44031794411297276
|
8 |
+
8,70,GPN_final.LogisticRegression.chrom,0.3240440115440115
|
9 |
+
9,240,GPN_final.LogisticRegression.chrom,0.1188968637404691
|
10 |
+
10,190,GPN_final.LogisticRegression.chrom,0.11279456426256373
|
11 |
+
11,480,GPN_final.LogisticRegression.chrom,0.5137398535568772
|
12 |
+
12,30,GPN_final.LogisticRegression.chrom,0.7380952380952381
|
13 |
+
13,210,GPN_final.LogisticRegression.chrom,0.2364931237786896
|
14 |
+
14,40,GPN_final.LogisticRegression.chrom,0.6394009216589862
|
15 |
+
16,80,GPN_final.LogisticRegression.chrom,0.25260196866301515
|
16 |
+
17,60,GPN_final.LogisticRegression.chrom,0.24977106227106224
|
17 |
+
19,400,GPN_final.LogisticRegression.chrom,0.7050770595376257
|
18 |
+
20,50,GPN_final.LogisticRegression.chrom,0.8625
|
19 |
+
22,20,GPN_final.LogisticRegression.chrom,0.3333333333333333
|
20 |
+
X,500,GPN_final.LogisticRegression.chrom,0.2377523034995725
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final_Embeddings.minus.inner_product.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN_final_Embeddings.minus.inner_product,0.13492557995316967
|
3 |
+
2,230,GPN_final_Embeddings.minus.inner_product,0.708601451146239
|
4 |
+
3,310,GPN_final_Embeddings.minus.inner_product,0.10960391167268393
|
5 |
+
5,20,GPN_final_Embeddings.minus.inner_product,0.08204334365325078
|
6 |
+
6,30,GPN_final_Embeddings.minus.inner_product,0.08630842841369157
|
7 |
+
7,210,GPN_final_Embeddings.minus.inner_product,0.42095020359596996
|
8 |
+
8,70,GPN_final_Embeddings.minus.inner_product,0.13143134516132227
|
9 |
+
9,240,GPN_final_Embeddings.minus.inner_product,0.28511297133422964
|
10 |
+
10,190,GPN_final_Embeddings.minus.inner_product,0.1474253652367575
|
11 |
+
11,480,GPN_final_Embeddings.minus.inner_product,0.07385808007993766
|
12 |
+
12,30,GPN_final_Embeddings.minus.inner_product,0.08409961685823755
|
13 |
+
13,210,GPN_final_Embeddings.minus.inner_product,0.12689948164254178
|
14 |
+
14,40,GPN_final_Embeddings.minus.inner_product,0.12614607614607615
|
15 |
+
16,80,GPN_final_Embeddings.minus.inner_product,0.18549456421107213
|
16 |
+
17,60,GPN_final_Embeddings.minus.inner_product,0.08391208633716957
|
17 |
+
19,400,GPN_final_Embeddings.minus.inner_product,0.0549725194081386
|
18 |
+
20,50,GPN_final_Embeddings.minus.inner_product,0.06912226409698605
|
19 |
+
22,20,GPN_final_Embeddings.minus.inner_product,0.11805555555555555
|
20 |
+
X,500,GPN_final_Embeddings.minus.inner_product,0.06277244093617562
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final_Embeddings.plus.euclidean_distance.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN_final_Embeddings.plus.euclidean_distance,0.24405206027665233
|
3 |
+
2,230,GPN_final_Embeddings.plus.euclidean_distance,0.3535972747193614
|
4 |
+
3,310,GPN_final_Embeddings.plus.euclidean_distance,0.15246903374217363
|
5 |
+
5,20,GPN_final_Embeddings.plus.euclidean_distance,1.0
|
6 |
+
6,30,GPN_final_Embeddings.plus.euclidean_distance,0.3055555555555556
|
7 |
+
7,210,GPN_final_Embeddings.plus.euclidean_distance,0.21506736793317
|
8 |
+
8,70,GPN_final_Embeddings.plus.euclidean_distance,0.13973667389033534
|
9 |
+
9,240,GPN_final_Embeddings.plus.euclidean_distance,0.11569387691779527
|
10 |
+
10,190,GPN_final_Embeddings.plus.euclidean_distance,0.1487761326178691
|
11 |
+
11,480,GPN_final_Embeddings.plus.euclidean_distance,0.3116219895820363
|
12 |
+
12,30,GPN_final_Embeddings.plus.euclidean_distance,0.5588235294117647
|
13 |
+
13,210,GPN_final_Embeddings.plus.euclidean_distance,0.4859724525641466
|
14 |
+
14,40,GPN_final_Embeddings.plus.euclidean_distance,0.14406565656565656
|
15 |
+
16,80,GPN_final_Embeddings.plus.euclidean_distance,0.45253891941391944
|
16 |
+
17,60,GPN_final_Embeddings.plus.euclidean_distance,0.6373015873015873
|
17 |
+
19,400,GPN_final_Embeddings.plus.euclidean_distance,0.3223197194646196
|
18 |
+
20,50,GPN_final_Embeddings.plus.euclidean_distance,0.5903703703703704
|
19 |
+
22,20,GPN_final_Embeddings.plus.euclidean_distance,0.5833333333333333
|
20 |
+
X,500,GPN_final_Embeddings.plus.euclidean_distance,0.6547619106022552
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final_InnerProduct.minus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN_final_InnerProduct.minus.score,0.13492557995316967
|
3 |
+
2,230,GPN_final_InnerProduct.minus.score,0.708601451146239
|
4 |
+
3,310,GPN_final_InnerProduct.minus.score,0.10960391167268393
|
5 |
+
5,20,GPN_final_InnerProduct.minus.score,0.08204334365325078
|
6 |
+
6,30,GPN_final_InnerProduct.minus.score,0.08630842841369157
|
7 |
+
7,210,GPN_final_InnerProduct.minus.score,0.42095020359596996
|
8 |
+
8,70,GPN_final_InnerProduct.minus.score,0.13143134516132227
|
9 |
+
9,240,GPN_final_InnerProduct.minus.score,0.28377750124875956
|
10 |
+
10,190,GPN_final_InnerProduct.minus.score,0.1474253652367575
|
11 |
+
11,480,GPN_final_InnerProduct.minus.score,0.07385808007993766
|
12 |
+
12,30,GPN_final_InnerProduct.minus.score,0.08409961685823755
|
13 |
+
13,210,GPN_final_InnerProduct.minus.score,0.12689948164254178
|
14 |
+
14,40,GPN_final_InnerProduct.minus.score,0.12614607614607615
|
15 |
+
16,80,GPN_final_InnerProduct.minus.score,0.18549456421107213
|
16 |
+
17,60,GPN_final_InnerProduct.minus.score,0.08391208633716957
|
17 |
+
19,400,GPN_final_InnerProduct.minus.score,0.05497363548855997
|
18 |
+
20,50,GPN_final_InnerProduct.minus.score,0.06912226409698605
|
19 |
+
22,20,GPN_final_InnerProduct.minus.score,0.11805555555555555
|
20 |
+
X,500,GPN_final_InnerProduct.minus.score,0.06277244093617562
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final_LLR.minus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
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|
|
|
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|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN_final_LLR.minus.score,0.3061106418445527
|
3 |
+
2,230,GPN_final_LLR.minus.score,0.36759162511851184
|
4 |
+
3,310,GPN_final_LLR.minus.score,0.1949614226614742
|
5 |
+
5,20,GPN_final_LLR.minus.score,0.10555555555555556
|
6 |
+
6,30,GPN_final_LLR.minus.score,0.26884920634920634
|
7 |
+
7,210,GPN_final_LLR.minus.score,0.185400685084673
|
8 |
+
8,70,GPN_final_LLR.minus.score,0.2235260750068052
|
9 |
+
9,240,GPN_final_LLR.minus.score,0.09996553154580928
|
10 |
+
10,190,GPN_final_LLR.minus.score,0.14067136761883764
|
11 |
+
11,480,GPN_final_LLR.minus.score,0.46989187526079607
|
12 |
+
12,30,GPN_final_LLR.minus.score,0.7291666666666666
|
13 |
+
13,210,GPN_final_LLR.minus.score,0.47488281555483164
|
14 |
+
14,40,GPN_final_LLR.minus.score,0.32717785843920144
|
15 |
+
16,80,GPN_final_LLR.minus.score,0.2120625002201506
|
16 |
+
17,60,GPN_final_LLR.minus.score,0.44076334936490313
|
17 |
+
19,400,GPN_final_LLR.minus.score,0.9049015951154109
|
18 |
+
20,50,GPN_final_LLR.minus.score,0.7259259259259259
|
19 |
+
22,20,GPN_final_LLR.minus.score,0.5909090909090909
|
20 |
+
X,500,GPN_final_LLR.minus.score,0.5736009850735719
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/GPN_final_absLLR.plus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
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|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,GPN_final_absLLR.plus.score,0.28076831775747374
|
3 |
+
2,230,GPN_final_absLLR.plus.score,0.29429125798258315
|
4 |
+
3,310,GPN_final_absLLR.plus.score,0.14248039614364344
|
5 |
+
5,20,GPN_final_absLLR.plus.score,0.34090909090909094
|
6 |
+
6,30,GPN_final_absLLR.plus.score,0.22777777777777777
|
7 |
+
7,210,GPN_final_absLLR.plus.score,0.13240025217888957
|
8 |
+
8,70,GPN_final_absLLR.plus.score,0.22635056755963406
|
9 |
+
9,240,GPN_final_absLLR.plus.score,0.07585850733327992
|
10 |
+
10,190,GPN_final_absLLR.plus.score,0.09813154797524926
|
11 |
+
11,480,GPN_final_absLLR.plus.score,0.40373467890028125
|
12 |
+
12,30,GPN_final_absLLR.plus.score,0.7037037037037037
|
13 |
+
13,210,GPN_final_absLLR.plus.score,0.4497213502196809
|
14 |
+
14,40,GPN_final_absLLR.plus.score,0.44107142857142856
|
15 |
+
16,80,GPN_final_absLLR.plus.score,0.2513946846914007
|
16 |
+
17,60,GPN_final_absLLR.plus.score,0.4430035650623886
|
17 |
+
19,400,GPN_final_absLLR.plus.score,0.8618089257548569
|
18 |
+
20,50,GPN_final_absLLR.plus.score,0.5756410256410256
|
19 |
+
22,20,GPN_final_absLLR.plus.score,0.5666666666666667
|
20 |
+
X,500,GPN_final_absLLR.plus.score,0.513820914469071
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA.LogisticRegression.chrom.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,HyenaDNA.LogisticRegression.chrom,0.15670488543604738
|
3 |
+
2,230,HyenaDNA.LogisticRegression.chrom,0.1814715464816507
|
4 |
+
3,310,HyenaDNA.LogisticRegression.chrom,0.07096387091424948
|
5 |
+
5,20,HyenaDNA.LogisticRegression.chrom,0.10101010101010101
|
6 |
+
6,30,HyenaDNA.LogisticRegression.chrom,0.22679045092838196
|
7 |
+
7,210,HyenaDNA.LogisticRegression.chrom,0.1529469796108884
|
8 |
+
8,70,HyenaDNA.LogisticRegression.chrom,0.10756621254392734
|
9 |
+
9,240,HyenaDNA.LogisticRegression.chrom,0.07955690503377709
|
10 |
+
10,190,HyenaDNA.LogisticRegression.chrom,0.10584472780349395
|
11 |
+
11,480,HyenaDNA.LogisticRegression.chrom,0.11916932551002471
|
12 |
+
12,30,HyenaDNA.LogisticRegression.chrom,0.12220893141945774
|
13 |
+
13,210,HyenaDNA.LogisticRegression.chrom,0.21680583702168982
|
14 |
+
14,40,HyenaDNA.LogisticRegression.chrom,0.1041796066252588
|
15 |
+
16,80,HyenaDNA.LogisticRegression.chrom,0.2328035533983341
|
16 |
+
17,60,HyenaDNA.LogisticRegression.chrom,0.1463345864661654
|
17 |
+
19,400,HyenaDNA.LogisticRegression.chrom,0.15255133821470782
|
18 |
+
20,50,HyenaDNA.LogisticRegression.chrom,0.12857002695115552
|
19 |
+
22,20,HyenaDNA.LogisticRegression.chrom,0.11688311688311688
|
20 |
+
X,500,HyenaDNA.LogisticRegression.chrom,0.20042824823524313
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_Embeddings.minus.inner_product.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,HyenaDNA_Embeddings.minus.inner_product,0.0955502181898374
|
3 |
+
2,230,HyenaDNA_Embeddings.minus.inner_product,0.43120571408129316
|
4 |
+
3,310,HyenaDNA_Embeddings.minus.inner_product,0.06295346071949677
|
5 |
+
5,20,HyenaDNA_Embeddings.minus.inner_product,0.10833333333333334
|
6 |
+
6,30,HyenaDNA_Embeddings.minus.inner_product,0.4658119658119658
|
7 |
+
7,210,HyenaDNA_Embeddings.minus.inner_product,0.43722737179607835
|
8 |
+
8,70,HyenaDNA_Embeddings.minus.inner_product,0.17761583356746954
|
9 |
+
9,240,HyenaDNA_Embeddings.minus.inner_product,0.19861628079527596
|
10 |
+
10,190,HyenaDNA_Embeddings.minus.inner_product,0.16926488054149272
|
11 |
+
11,480,HyenaDNA_Embeddings.minus.inner_product,0.09544382316792864
|
12 |
+
12,30,HyenaDNA_Embeddings.minus.inner_product,0.13593813593813595
|
13 |
+
13,210,HyenaDNA_Embeddings.minus.inner_product,0.15237328671903677
|
14 |
+
14,40,HyenaDNA_Embeddings.minus.inner_product,0.11068423604574883
|
15 |
+
16,80,HyenaDNA_Embeddings.minus.inner_product,0.1686275023231545
|
16 |
+
17,60,HyenaDNA_Embeddings.minus.inner_product,0.08832710487741385
|
17 |
+
19,400,HyenaDNA_Embeddings.minus.inner_product,0.14209708070720461
|
18 |
+
20,50,HyenaDNA_Embeddings.minus.inner_product,0.11100088323617735
|
19 |
+
22,20,HyenaDNA_Embeddings.minus.inner_product,0.11858974358974358
|
20 |
+
X,500,HyenaDNA_Embeddings.minus.inner_product,0.09647085693141619
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_Embeddings.plus.cosine_distance.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,HyenaDNA_Embeddings.plus.cosine_distance,0.0953794122274706
|
3 |
+
2,230,HyenaDNA_Embeddings.plus.cosine_distance,0.1043475295273979
|
4 |
+
3,310,HyenaDNA_Embeddings.plus.cosine_distance,0.2149450094468946
|
5 |
+
5,20,HyenaDNA_Embeddings.plus.cosine_distance,0.25
|
6 |
+
6,30,HyenaDNA_Embeddings.plus.cosine_distance,0.1267543859649123
|
7 |
+
7,210,HyenaDNA_Embeddings.plus.cosine_distance,0.06660807129994017
|
8 |
+
8,70,HyenaDNA_Embeddings.plus.cosine_distance,0.0785860793557838
|
9 |
+
9,240,HyenaDNA_Embeddings.plus.cosine_distance,0.07236679482266054
|
10 |
+
10,190,HyenaDNA_Embeddings.plus.cosine_distance,0.1948121822413617
|
11 |
+
11,480,HyenaDNA_Embeddings.plus.cosine_distance,0.13916756089550494
|
12 |
+
12,30,HyenaDNA_Embeddings.plus.cosine_distance,0.08543123543123543
|
13 |
+
13,210,HyenaDNA_Embeddings.plus.cosine_distance,0.08485658187590216
|
14 |
+
14,40,HyenaDNA_Embeddings.plus.cosine_distance,0.14110669024462127
|
15 |
+
16,80,HyenaDNA_Embeddings.plus.cosine_distance,0.07262743465778027
|
16 |
+
17,60,HyenaDNA_Embeddings.plus.cosine_distance,0.10592818291247832
|
17 |
+
19,400,HyenaDNA_Embeddings.plus.cosine_distance,0.07251566477682994
|
18 |
+
20,50,HyenaDNA_Embeddings.plus.cosine_distance,0.1513997113997114
|
19 |
+
22,20,HyenaDNA_Embeddings.plus.cosine_distance,0.10263157894736842
|
20 |
+
X,500,HyenaDNA_Embeddings.plus.cosine_distance,0.11296786229813316
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_Embeddings.plus.euclidean_distance.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,HyenaDNA_Embeddings.plus.euclidean_distance,0.09896716769275145
|
3 |
+
2,230,HyenaDNA_Embeddings.plus.euclidean_distance,0.09958293519406575
|
4 |
+
3,310,HyenaDNA_Embeddings.plus.euclidean_distance,0.23133002987436238
|
5 |
+
5,20,HyenaDNA_Embeddings.plus.euclidean_distance,0.25
|
6 |
+
6,30,HyenaDNA_Embeddings.plus.euclidean_distance,0.11604010025062655
|
7 |
+
7,210,HyenaDNA_Embeddings.plus.euclidean_distance,0.06980360257471241
|
8 |
+
8,70,HyenaDNA_Embeddings.plus.euclidean_distance,0.07811278242037192
|
9 |
+
9,240,HyenaDNA_Embeddings.plus.euclidean_distance,0.07216345460688102
|
10 |
+
10,190,HyenaDNA_Embeddings.plus.euclidean_distance,0.1764146986058967
|
11 |
+
11,480,HyenaDNA_Embeddings.plus.euclidean_distance,0.14226878425743705
|
12 |
+
12,30,HyenaDNA_Embeddings.plus.euclidean_distance,0.08543123543123543
|
13 |
+
13,210,HyenaDNA_Embeddings.plus.euclidean_distance,0.08505069354392486
|
14 |
+
14,40,HyenaDNA_Embeddings.plus.euclidean_distance,0.14233821733821733
|
15 |
+
16,80,HyenaDNA_Embeddings.plus.euclidean_distance,0.07256214371441337
|
16 |
+
17,60,HyenaDNA_Embeddings.plus.euclidean_distance,0.10604803289135087
|
17 |
+
19,400,HyenaDNA_Embeddings.plus.euclidean_distance,0.07166764533521094
|
18 |
+
20,50,HyenaDNA_Embeddings.plus.euclidean_distance,0.1447330447330447
|
19 |
+
22,20,HyenaDNA_Embeddings.plus.euclidean_distance,0.10263157894736842
|
20 |
+
X,500,HyenaDNA_Embeddings.plus.euclidean_distance,0.11144262328769536
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_InnerProduct.minus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,HyenaDNA_InnerProduct.minus.score,0.0955502181898374
|
3 |
+
2,230,HyenaDNA_InnerProduct.minus.score,0.43120571408129316
|
4 |
+
3,310,HyenaDNA_InnerProduct.minus.score,0.06294375977535238
|
5 |
+
5,20,HyenaDNA_InnerProduct.minus.score,0.10833333333333334
|
6 |
+
6,30,HyenaDNA_InnerProduct.minus.score,0.4658119658119658
|
7 |
+
7,210,HyenaDNA_InnerProduct.minus.score,0.43722737179607835
|
8 |
+
8,70,HyenaDNA_InnerProduct.minus.score,0.17761583356746954
|
9 |
+
9,240,HyenaDNA_InnerProduct.minus.score,0.19861628079527596
|
10 |
+
10,190,HyenaDNA_InnerProduct.minus.score,0.16926488054149272
|
11 |
+
11,480,HyenaDNA_InnerProduct.minus.score,0.09544923400171648
|
12 |
+
12,30,HyenaDNA_InnerProduct.minus.score,0.13593813593813595
|
13 |
+
13,210,HyenaDNA_InnerProduct.minus.score,0.15237328671903677
|
14 |
+
14,40,HyenaDNA_InnerProduct.minus.score,0.11068423604574883
|
15 |
+
16,80,HyenaDNA_InnerProduct.minus.score,0.1686275023231545
|
16 |
+
17,60,HyenaDNA_InnerProduct.minus.score,0.08832710487741385
|
17 |
+
19,400,HyenaDNA_InnerProduct.minus.score,0.14209708070720461
|
18 |
+
20,50,HyenaDNA_InnerProduct.minus.score,0.11100088323617735
|
19 |
+
22,20,HyenaDNA_InnerProduct.minus.score,0.11858974358974358
|
20 |
+
X,500,HyenaDNA_InnerProduct.minus.score,0.09647085693141619
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_LLR.minus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,HyenaDNA_LLR.minus.score,0.10807334177498161
|
3 |
+
2,230,HyenaDNA_LLR.minus.score,0.10019614501048404
|
4 |
+
3,310,HyenaDNA_LLR.minus.score,0.14719544726080497
|
5 |
+
5,20,HyenaDNA_LLR.minus.score,0.11688311688311688
|
6 |
+
6,30,HyenaDNA_LLR.minus.score,0.09543123543123544
|
7 |
+
7,210,HyenaDNA_LLR.minus.score,0.15145153975838294
|
8 |
+
8,70,HyenaDNA_LLR.minus.score,0.14769118430422276
|
9 |
+
9,240,HyenaDNA_LLR.minus.score,0.09768185885106559
|
10 |
+
10,190,HyenaDNA_LLR.minus.score,0.10357678876324306
|
11 |
+
11,480,HyenaDNA_LLR.minus.score,0.09247693828176817
|
12 |
+
12,30,HyenaDNA_LLR.minus.score,0.24166666666666667
|
13 |
+
13,210,HyenaDNA_LLR.minus.score,0.14229966068563588
|
14 |
+
14,40,HyenaDNA_LLR.minus.score,0.17945431761221234
|
15 |
+
16,80,HyenaDNA_LLR.minus.score,0.09052502647021195
|
16 |
+
17,60,HyenaDNA_LLR.minus.score,0.10490026278069756
|
17 |
+
19,400,HyenaDNA_LLR.minus.score,0.10228290321693309
|
18 |
+
20,50,HyenaDNA_LLR.minus.score,0.11422317992085433
|
19 |
+
22,20,HyenaDNA_LLR.minus.score,0.1125
|
20 |
+
X,500,HyenaDNA_LLR.minus.score,0.1128907108933543
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/HyenaDNA_absLLR.plus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,HyenaDNA_absLLR.plus.score,0.10991619623459145
|
3 |
+
2,230,HyenaDNA_absLLR.plus.score,0.08706424598235879
|
4 |
+
3,310,HyenaDNA_absLLR.plus.score,0.09499216919244055
|
5 |
+
5,20,HyenaDNA_absLLR.plus.score,0.07941176470588235
|
6 |
+
6,30,HyenaDNA_absLLR.plus.score,0.12429971988795518
|
7 |
+
7,210,HyenaDNA_absLLR.plus.score,0.100906797080963
|
8 |
+
8,70,HyenaDNA_absLLR.plus.score,0.10069772915554896
|
9 |
+
9,240,HyenaDNA_absLLR.plus.score,0.0997512914221033
|
10 |
+
10,190,HyenaDNA_absLLR.plus.score,0.1474479264421917
|
11 |
+
11,480,HyenaDNA_absLLR.plus.score,0.08103852707290907
|
12 |
+
12,30,HyenaDNA_absLLR.plus.score,0.33448275862068966
|
13 |
+
13,210,HyenaDNA_absLLR.plus.score,0.12202624356478368
|
14 |
+
14,40,HyenaDNA_absLLR.plus.score,0.17500000000000002
|
15 |
+
16,80,HyenaDNA_absLLR.plus.score,0.08660405002618117
|
16 |
+
17,60,HyenaDNA_absLLR.plus.score,0.10142532813833707
|
17 |
+
19,400,HyenaDNA_absLLR.plus.score,0.09285181907630072
|
18 |
+
20,50,HyenaDNA_absLLR.plus.score,0.10911206440618207
|
19 |
+
22,20,HyenaDNA_absLLR.plus.score,0.2222222222222222
|
20 |
+
X,500,HyenaDNA_absLLR.plus.score,0.12046291552805939
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer.LogisticRegression.chrom.csv
ADDED
@@ -0,0 +1,20 @@
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,NucleotideTransformer.LogisticRegression.chrom,0.13815013765173423
|
3 |
+
2,230,NucleotideTransformer.LogisticRegression.chrom,0.19548580272797536
|
4 |
+
3,310,NucleotideTransformer.LogisticRegression.chrom,0.2090987228511961
|
5 |
+
5,20,NucleotideTransformer.LogisticRegression.chrom,0.15476190476190477
|
6 |
+
6,30,NucleotideTransformer.LogisticRegression.chrom,0.1384032634032634
|
7 |
+
7,210,NucleotideTransformer.LogisticRegression.chrom,0.21003016081628056
|
8 |
+
8,70,NucleotideTransformer.LogisticRegression.chrom,0.2385560867703725
|
9 |
+
9,240,NucleotideTransformer.LogisticRegression.chrom,0.0635770937028757
|
10 |
+
10,190,NucleotideTransformer.LogisticRegression.chrom,0.10504762380978767
|
11 |
+
11,480,NucleotideTransformer.LogisticRegression.chrom,0.15962080021667815
|
12 |
+
12,30,NucleotideTransformer.LogisticRegression.chrom,0.1439814814814815
|
13 |
+
13,210,NucleotideTransformer.LogisticRegression.chrom,0.0844409062078227
|
14 |
+
14,40,NucleotideTransformer.LogisticRegression.chrom,0.3774509803921569
|
15 |
+
16,80,NucleotideTransformer.LogisticRegression.chrom,0.19530026511860693
|
16 |
+
17,60,NucleotideTransformer.LogisticRegression.chrom,0.08581161015382376
|
17 |
+
19,400,NucleotideTransformer.LogisticRegression.chrom,0.3834137353609347
|
18 |
+
20,50,NucleotideTransformer.LogisticRegression.chrom,0.15973856209150328
|
19 |
+
22,20,NucleotideTransformer.LogisticRegression.chrom,0.13025210084033612
|
20 |
+
X,500,NucleotideTransformer.LogisticRegression.chrom,0.07393262089207808
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer_Embeddings.minus.inner_product.csv
ADDED
@@ -0,0 +1,20 @@
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,NucleotideTransformer_Embeddings.minus.inner_product,0.11103326051613768
|
3 |
+
2,230,NucleotideTransformer_Embeddings.minus.inner_product,0.13498331445317718
|
4 |
+
3,310,NucleotideTransformer_Embeddings.minus.inner_product,0.11198747790845587
|
5 |
+
5,20,NucleotideTransformer_Embeddings.minus.inner_product,0.3214285714285714
|
6 |
+
6,30,NucleotideTransformer_Embeddings.minus.inner_product,0.1288888888888889
|
7 |
+
7,210,NucleotideTransformer_Embeddings.minus.inner_product,0.06459990061420406
|
8 |
+
8,70,NucleotideTransformer_Embeddings.minus.inner_product,0.6579931972789115
|
9 |
+
9,240,NucleotideTransformer_Embeddings.minus.inner_product,0.11091176503346026
|
10 |
+
10,190,NucleotideTransformer_Embeddings.minus.inner_product,0.09496092003145129
|
11 |
+
11,480,NucleotideTransformer_Embeddings.minus.inner_product,0.11696383814695947
|
12 |
+
12,30,NucleotideTransformer_Embeddings.minus.inner_product,0.4555555555555555
|
13 |
+
13,210,NucleotideTransformer_Embeddings.minus.inner_product,0.2784483466782536
|
14 |
+
14,40,NucleotideTransformer_Embeddings.minus.inner_product,0.19089912280701754
|
15 |
+
16,80,NucleotideTransformer_Embeddings.minus.inner_product,0.10182027024699439
|
16 |
+
17,60,NucleotideTransformer_Embeddings.minus.inner_product,0.19212503446374413
|
17 |
+
19,400,NucleotideTransformer_Embeddings.minus.inner_product,0.47411980724754976
|
18 |
+
20,50,NucleotideTransformer_Embeddings.minus.inner_product,0.1596504884004884
|
19 |
+
22,20,NucleotideTransformer_Embeddings.minus.inner_product,0.6666666666666666
|
20 |
+
X,500,NucleotideTransformer_Embeddings.minus.inner_product,0.10959578588061097
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer_Embeddings.plus.euclidean_distance.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.12142875562239575
|
3 |
+
2,230,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.342889709510935
|
4 |
+
3,310,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.07233541359141428
|
5 |
+
5,20,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.41666666666666663
|
6 |
+
6,30,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.4714285714285714
|
7 |
+
7,210,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.17784671874117586
|
8 |
+
8,70,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.09297496776488375
|
9 |
+
9,240,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.09996597144229484
|
10 |
+
10,190,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.14227698178136905
|
11 |
+
11,480,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.16672530722735648
|
12 |
+
12,30,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.19771241830065361
|
13 |
+
13,210,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.10185996334259023
|
14 |
+
14,40,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.14849738075544527
|
15 |
+
16,80,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.35824843873599244
|
16 |
+
17,60,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.1388960310738261
|
17 |
+
19,400,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.23867214538718004
|
18 |
+
20,50,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.139257326007326
|
19 |
+
22,20,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.26785714285714285
|
20 |
+
X,500,NucleotideTransformer_Embeddings.plus.euclidean_distance,0.2640380223263519
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer_InnerProduct.minus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,NucleotideTransformer_InnerProduct.minus.score,0.11103326051613768
|
3 |
+
2,230,NucleotideTransformer_InnerProduct.minus.score,0.13498331445317718
|
4 |
+
3,310,NucleotideTransformer_InnerProduct.minus.score,0.11198747790845587
|
5 |
+
5,20,NucleotideTransformer_InnerProduct.minus.score,0.3214285714285714
|
6 |
+
6,30,NucleotideTransformer_InnerProduct.minus.score,0.1288888888888889
|
7 |
+
7,210,NucleotideTransformer_InnerProduct.minus.score,0.06459990061420406
|
8 |
+
8,70,NucleotideTransformer_InnerProduct.minus.score,0.6579931972789115
|
9 |
+
9,240,NucleotideTransformer_InnerProduct.minus.score,0.11091176503346026
|
10 |
+
10,190,NucleotideTransformer_InnerProduct.minus.score,0.09496092003145129
|
11 |
+
11,480,NucleotideTransformer_InnerProduct.minus.score,0.11696383814695947
|
12 |
+
12,30,NucleotideTransformer_InnerProduct.minus.score,0.4555555555555555
|
13 |
+
13,210,NucleotideTransformer_InnerProduct.minus.score,0.2784483466782536
|
14 |
+
14,40,NucleotideTransformer_InnerProduct.minus.score,0.19089912280701754
|
15 |
+
16,80,NucleotideTransformer_InnerProduct.minus.score,0.10182027024699439
|
16 |
+
17,60,NucleotideTransformer_InnerProduct.minus.score,0.19212503446374413
|
17 |
+
19,400,NucleotideTransformer_InnerProduct.minus.score,0.4736786307769615
|
18 |
+
20,50,NucleotideTransformer_InnerProduct.minus.score,0.1596504884004884
|
19 |
+
22,20,NucleotideTransformer_InnerProduct.minus.score,0.6666666666666666
|
20 |
+
X,500,NucleotideTransformer_InnerProduct.minus.score,0.10959578588061097
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer_LLR.minus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,NucleotideTransformer_LLR.minus.score,0.17681945780773214
|
3 |
+
2,230,NucleotideTransformer_LLR.minus.score,0.13593308351655256
|
4 |
+
3,310,NucleotideTransformer_LLR.minus.score,0.12172622964582658
|
5 |
+
5,20,NucleotideTransformer_LLR.minus.score,0.07941176470588235
|
6 |
+
6,30,NucleotideTransformer_LLR.minus.score,0.13179734918865355
|
7 |
+
7,210,NucleotideTransformer_LLR.minus.score,0.08527545659765474
|
8 |
+
8,70,NucleotideTransformer_LLR.minus.score,0.08187566721366091
|
9 |
+
9,240,NucleotideTransformer_LLR.minus.score,0.10361471577387191
|
10 |
+
10,190,NucleotideTransformer_LLR.minus.score,0.13981952821706572
|
11 |
+
11,480,NucleotideTransformer_LLR.minus.score,0.13111728053156868
|
12 |
+
12,30,NucleotideTransformer_LLR.minus.score,0.1643097643097643
|
13 |
+
13,210,NucleotideTransformer_LLR.minus.score,0.12291781778580468
|
14 |
+
14,40,NucleotideTransformer_LLR.minus.score,0.09109936789846834
|
15 |
+
16,80,NucleotideTransformer_LLR.minus.score,0.11971918072945976
|
16 |
+
17,60,NucleotideTransformer_LLR.minus.score,0.13849418125733914
|
17 |
+
19,400,NucleotideTransformer_LLR.minus.score,0.10426382397564313
|
18 |
+
20,50,NucleotideTransformer_LLR.minus.score,0.10723977172253034
|
19 |
+
22,20,NucleotideTransformer_LLR.minus.score,0.10989010989010989
|
20 |
+
X,500,NucleotideTransformer_LLR.minus.score,0.10849701761085975
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/NucleotideTransformer_absLLR.plus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,NucleotideTransformer_absLLR.plus.score,0.16298778622468482
|
3 |
+
2,230,NucleotideTransformer_absLLR.plus.score,0.08278574428165184
|
4 |
+
3,310,NucleotideTransformer_absLLR.plus.score,0.08668495605277289
|
5 |
+
5,20,NucleotideTransformer_absLLR.plus.score,0.1588235294117647
|
6 |
+
6,30,NucleotideTransformer_absLLR.plus.score,0.09758771929824561
|
7 |
+
7,210,NucleotideTransformer_absLLR.plus.score,0.08466828931992398
|
8 |
+
8,70,NucleotideTransformer_absLLR.plus.score,0.07662781950843119
|
9 |
+
9,240,NucleotideTransformer_absLLR.plus.score,0.07662700699132557
|
10 |
+
10,190,NucleotideTransformer_absLLR.plus.score,0.09123095190470865
|
11 |
+
11,480,NucleotideTransformer_absLLR.plus.score,0.10052290855122237
|
12 |
+
12,30,NucleotideTransformer_absLLR.plus.score,0.16015466015466015
|
13 |
+
13,210,NucleotideTransformer_absLLR.plus.score,0.09019459062824878
|
14 |
+
14,40,NucleotideTransformer_absLLR.plus.score,0.16125541125541126
|
15 |
+
16,80,NucleotideTransformer_absLLR.plus.score,0.14210954789412236
|
16 |
+
17,60,NucleotideTransformer_absLLR.plus.score,0.16848318159059847
|
17 |
+
19,400,NucleotideTransformer_absLLR.plus.score,0.07060609907258486
|
18 |
+
20,50,NucleotideTransformer_absLLR.plus.score,0.0823550947408521
|
19 |
+
22,20,NucleotideTransformer_absLLR.plus.score,0.07631578947368421
|
20 |
+
X,500,NucleotideTransformer_absLLR.plus.score,0.10506481674078275
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/Sei.LogisticRegression.chrom.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,Sei.LogisticRegression.chrom,0.2009180375683519
|
3 |
+
2,230,Sei.LogisticRegression.chrom,0.5160861655202625
|
4 |
+
3,310,Sei.LogisticRegression.chrom,0.3531604384397623
|
5 |
+
5,20,Sei.LogisticRegression.chrom,0.2777777777777778
|
6 |
+
6,30,Sei.LogisticRegression.chrom,0.13788335847159378
|
7 |
+
7,210,Sei.LogisticRegression.chrom,0.19600052863294015
|
8 |
+
8,70,Sei.LogisticRegression.chrom,0.17275576897425637
|
9 |
+
9,240,Sei.LogisticRegression.chrom,0.42272313750896495
|
10 |
+
10,190,Sei.LogisticRegression.chrom,0.21672087290597336
|
11 |
+
11,480,Sei.LogisticRegression.chrom,0.27259711583533186
|
12 |
+
12,30,Sei.LogisticRegression.chrom,0.7051282051282051
|
13 |
+
13,210,Sei.LogisticRegression.chrom,0.5172626733688165
|
14 |
+
14,40,Sei.LogisticRegression.chrom,0.1273399014778325
|
15 |
+
16,80,Sei.LogisticRegression.chrom,0.13815786392630655
|
16 |
+
17,60,Sei.LogisticRegression.chrom,0.3142968142968143
|
17 |
+
19,400,Sei.LogisticRegression.chrom,0.33748630036807903
|
18 |
+
20,50,Sei.LogisticRegression.chrom,0.5856280193236716
|
19 |
+
22,20,Sei.LogisticRegression.chrom,0.3333333333333333
|
20 |
+
X,500,Sei.LogisticRegression.chrom,0.4716411959150835
|
mendelian_traits_matched_9/AUPRC_by_chrom/all/Sei.plus.seqclass_max_absdiff.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,210,Sei.plus.seqclass_max_absdiff,0.16468034385858493
|
3 |
+
2,230,Sei.plus.seqclass_max_absdiff,0.403645660362569
|
4 |
+
3,310,Sei.plus.seqclass_max_absdiff,0.3611951384504311
|
5 |
+
5,20,Sei.plus.seqclass_max_absdiff,0.5588235294117647
|
6 |
+
6,30,Sei.plus.seqclass_max_absdiff,0.13849016480595427
|
7 |
+
7,210,Sei.plus.seqclass_max_absdiff,0.20594887459461234
|
8 |
+
8,70,Sei.plus.seqclass_max_absdiff,0.2065103369467696
|
9 |
+
9,240,Sei.plus.seqclass_max_absdiff,0.5051879888916634
|
10 |
+
10,190,Sei.plus.seqclass_max_absdiff,0.23984422090938615
|
11 |
+
11,480,Sei.plus.seqclass_max_absdiff,0.1987274653805728
|
12 |
+
12,30,Sei.plus.seqclass_max_absdiff,0.7222222222222222
|
13 |
+
13,210,Sei.plus.seqclass_max_absdiff,0.41942342748371236
|
14 |
+
14,40,Sei.plus.seqclass_max_absdiff,0.08549432267671832
|
15 |
+
16,80,Sei.plus.seqclass_max_absdiff,0.25348149573881745
|
16 |
+
17,60,Sei.plus.seqclass_max_absdiff,0.1850187356066492
|
17 |
+
19,400,Sei.plus.seqclass_max_absdiff,0.259604972302454
|
18 |
+
20,50,Sei.plus.seqclass_max_absdiff,0.32855436081242534
|
19 |
+
22,20,Sei.plus.seqclass_max_absdiff,0.30952380952380953
|
20 |
+
X,500,Sei.plus.seqclass_max_absdiff,0.27639038472704436
|
mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Borzoi.LogisticRegression.chrom.subset_from_all.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,180,Borzoi.LogisticRegression.chrom.subset_from_all,0.29180902075533965
|
3 |
+
2,210,Borzoi.LogisticRegression.chrom.subset_from_all,0.35047453388166727
|
4 |
+
3,290,Borzoi.LogisticRegression.chrom.subset_from_all,0.4798329943710353
|
5 |
+
5,20,Borzoi.LogisticRegression.chrom.subset_from_all,0.10238095238095238
|
6 |
+
6,30,Borzoi.LogisticRegression.chrom.subset_from_all,0.8055555555555556
|
7 |
+
7,190,Borzoi.LogisticRegression.chrom.subset_from_all,0.22733971088209398
|
8 |
+
8,60,Borzoi.LogisticRegression.chrom.subset_from_all,0.2979664014146773
|
9 |
+
9,220,Borzoi.LogisticRegression.chrom.subset_from_all,0.45246146901044415
|
10 |
+
10,170,Borzoi.LogisticRegression.chrom.subset_from_all,0.30473478105720864
|
11 |
+
11,400,Borzoi.LogisticRegression.chrom.subset_from_all,0.5506176649628874
|
12 |
+
12,30,Borzoi.LogisticRegression.chrom.subset_from_all,0.7142857142857142
|
13 |
+
13,200,Borzoi.LogisticRegression.chrom.subset_from_all,0.4534679261735189
|
14 |
+
14,40,Borzoi.LogisticRegression.chrom.subset_from_all,0.14066176470588235
|
15 |
+
16,60,Borzoi.LogisticRegression.chrom.subset_from_all,0.8436507936507935
|
16 |
+
17,50,Borzoi.LogisticRegression.chrom.subset_from_all,0.21278140115462632
|
17 |
+
19,350,Borzoi.LogisticRegression.chrom.subset_from_all,0.515223469188229
|
18 |
+
20,30,Borzoi.LogisticRegression.chrom.subset_from_all,1.0
|
19 |
+
22,20,Borzoi.LogisticRegression.chrom.subset_from_all,1.0
|
20 |
+
X,500,Borzoi.LogisticRegression.chrom.subset_from_all,0.595317006258727
|
mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Borzoi_L2_L2.plus.all.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,180,Borzoi_L2_L2.plus.all,0.219759223810597
|
3 |
+
2,210,Borzoi_L2_L2.plus.all,0.3505842585557289
|
4 |
+
3,290,Borzoi_L2_L2.plus.all,0.2952610929118675
|
5 |
+
5,20,Borzoi_L2_L2.plus.all,0.5666666666666667
|
6 |
+
6,30,Borzoi_L2_L2.plus.all,0.9166666666666665
|
7 |
+
7,190,Borzoi_L2_L2.plus.all,0.1673808321532231
|
8 |
+
8,60,Borzoi_L2_L2.plus.all,0.192687327456235
|
9 |
+
9,220,Borzoi_L2_L2.plus.all,0.35922449949783575
|
10 |
+
10,170,Borzoi_L2_L2.plus.all,0.22583518486319437
|
11 |
+
11,400,Borzoi_L2_L2.plus.all,0.41496899954225724
|
12 |
+
12,30,Borzoi_L2_L2.plus.all,0.6031746031746031
|
13 |
+
13,200,Borzoi_L2_L2.plus.all,0.6294010409270047
|
14 |
+
14,40,Borzoi_L2_L2.plus.all,0.11122362357506668
|
15 |
+
16,60,Borzoi_L2_L2.plus.all,0.5779914529914529
|
16 |
+
17,50,Borzoi_L2_L2.plus.all,0.2629166666666667
|
17 |
+
19,350,Borzoi_L2_L2.plus.all,0.36704377229214646
|
18 |
+
20,30,Borzoi_L2_L2.plus.all,0.8095238095238095
|
19 |
+
22,20,Borzoi_L2_L2.plus.all,1.0
|
20 |
+
X,500,Borzoi_L2_L2.plus.all,0.6999088348317529
|
mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/CADD.LogisticRegression.chrom.subset_from_all.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,180,CADD.LogisticRegression.chrom.subset_from_all,0.7200424570087128
|
3 |
+
2,210,CADD.LogisticRegression.chrom.subset_from_all,0.9806525308774185
|
4 |
+
3,290,CADD.LogisticRegression.chrom.subset_from_all,0.9748630759406621
|
5 |
+
5,20,CADD.LogisticRegression.chrom.subset_from_all,0.5833333333333333
|
6 |
+
6,30,CADD.LogisticRegression.chrom.subset_from_all,0.5555555555555556
|
7 |
+
7,190,CADD.LogisticRegression.chrom.subset_from_all,0.9706242350061196
|
8 |
+
8,60,CADD.LogisticRegression.chrom.subset_from_all,1.0
|
9 |
+
9,220,CADD.LogisticRegression.chrom.subset_from_all,0.879176262060358
|
10 |
+
10,170,CADD.LogisticRegression.chrom.subset_from_all,0.7004401987334501
|
11 |
+
11,400,CADD.LogisticRegression.chrom.subset_from_all,0.7652453305840552
|
12 |
+
12,30,CADD.LogisticRegression.chrom.subset_from_all,1.0
|
13 |
+
13,200,CADD.LogisticRegression.chrom.subset_from_all,0.8238854574196859
|
14 |
+
14,40,CADD.LogisticRegression.chrom.subset_from_all,0.40929487179487173
|
15 |
+
16,60,CADD.LogisticRegression.chrom.subset_from_all,0.5471153846153846
|
16 |
+
17,50,CADD.LogisticRegression.chrom.subset_from_all,0.8500000000000001
|
17 |
+
19,350,CADD.LogisticRegression.chrom.subset_from_all,0.9636772424892017
|
18 |
+
20,30,CADD.LogisticRegression.chrom.subset_from_all,1.0
|
19 |
+
22,20,CADD.LogisticRegression.chrom.subset_from_all,1.0
|
20 |
+
X,500,CADD.LogisticRegression.chrom.subset_from_all,0.9562419987319039
|
mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/CADD.plus.RawScore.csv
ADDED
@@ -0,0 +1,20 @@
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,180,CADD.plus.RawScore,0.3520614308724163
|
3 |
+
2,210,CADD.plus.RawScore,0.8032959657945107
|
4 |
+
3,290,CADD.plus.RawScore,0.8622017073464916
|
5 |
+
5,20,CADD.plus.RawScore,0.3088235294117647
|
6 |
+
6,30,CADD.plus.RawScore,0.2415966386554622
|
7 |
+
7,190,CADD.plus.RawScore,0.9004274909970391
|
8 |
+
8,60,CADD.plus.RawScore,0.4235514381191072
|
9 |
+
9,220,CADD.plus.RawScore,0.7549191696122322
|
10 |
+
10,170,CADD.plus.RawScore,0.5723441504246553
|
11 |
+
11,400,CADD.plus.RawScore,0.6094792947184097
|
12 |
+
12,30,CADD.plus.RawScore,1.0
|
13 |
+
13,200,CADD.plus.RawScore,0.6540448864827161
|
14 |
+
14,40,CADD.plus.RawScore,0.13773148148148145
|
15 |
+
16,60,CADD.plus.RawScore,0.719298245614035
|
16 |
+
17,50,CADD.plus.RawScore,0.6666666666666666
|
17 |
+
19,350,CADD.plus.RawScore,0.9021124909608754
|
18 |
+
20,30,CADD.plus.RawScore,1.0
|
19 |
+
22,20,CADD.plus.RawScore,1.0
|
20 |
+
X,500,CADD.plus.RawScore,0.7296850544024586
|
mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Caduceus.LogisticRegression.chrom.subset_from_all.csv
ADDED
@@ -0,0 +1,20 @@
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|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,180,Caduceus.LogisticRegression.chrom.subset_from_all,0.11135257324040507
|
3 |
+
2,210,Caduceus.LogisticRegression.chrom.subset_from_all,0.09914843575658305
|
4 |
+
3,290,Caduceus.LogisticRegression.chrom.subset_from_all,0.6415782608168864
|
5 |
+
5,20,Caduceus.LogisticRegression.chrom.subset_from_all,0.11437908496732026
|
6 |
+
6,30,Caduceus.LogisticRegression.chrom.subset_from_all,0.14825174825174825
|
7 |
+
7,190,Caduceus.LogisticRegression.chrom.subset_from_all,0.8009435352191296
|
8 |
+
8,60,Caduceus.LogisticRegression.chrom.subset_from_all,0.30322373704726646
|
9 |
+
9,220,Caduceus.LogisticRegression.chrom.subset_from_all,0.0912598504122277
|
10 |
+
10,170,Caduceus.LogisticRegression.chrom.subset_from_all,0.2519573444286153
|
11 |
+
11,400,Caduceus.LogisticRegression.chrom.subset_from_all,0.07204192462096931
|
12 |
+
12,30,Caduceus.LogisticRegression.chrom.subset_from_all,0.2148148148148148
|
13 |
+
13,200,Caduceus.LogisticRegression.chrom.subset_from_all,0.3767058574002248
|
14 |
+
14,40,Caduceus.LogisticRegression.chrom.subset_from_all,0.5629117259552042
|
15 |
+
16,60,Caduceus.LogisticRegression.chrom.subset_from_all,0.22422791580400278
|
16 |
+
17,50,Caduceus.LogisticRegression.chrom.subset_from_all,0.21089466089466088
|
17 |
+
19,350,Caduceus.LogisticRegression.chrom.subset_from_all,0.13392269763078107
|
18 |
+
20,30,Caduceus.LogisticRegression.chrom.subset_from_all,0.34444444444444444
|
19 |
+
22,20,Caduceus.LogisticRegression.chrom.subset_from_all,0.09821428571428571
|
20 |
+
X,500,Caduceus.LogisticRegression.chrom.subset_from_all,0.09254823352244966
|
mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Caduceus_Embeddings.minus.inner_product.csv
ADDED
@@ -0,0 +1,20 @@
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,180,Caduceus_Embeddings.minus.inner_product,0.16628662075948905
|
3 |
+
2,210,Caduceus_Embeddings.minus.inner_product,0.18265238541661527
|
4 |
+
3,290,Caduceus_Embeddings.minus.inner_product,0.12791467485024685
|
5 |
+
5,20,Caduceus_Embeddings.minus.inner_product,0.5714285714285714
|
6 |
+
6,30,Caduceus_Embeddings.minus.inner_product,0.148109243697479
|
7 |
+
7,190,Caduceus_Embeddings.minus.inner_product,0.13329210692928029
|
8 |
+
8,60,Caduceus_Embeddings.minus.inner_product,0.06951112228711714
|
9 |
+
9,220,Caduceus_Embeddings.minus.inner_product,0.17446552024870704
|
10 |
+
10,170,Caduceus_Embeddings.minus.inner_product,0.08616795160103485
|
11 |
+
11,400,Caduceus_Embeddings.minus.inner_product,0.06873000214250304
|
12 |
+
12,30,Caduceus_Embeddings.minus.inner_product,0.7192982456140351
|
13 |
+
13,200,Caduceus_Embeddings.minus.inner_product,0.11895285747760828
|
14 |
+
14,40,Caduceus_Embeddings.minus.inner_product,0.10082877648667121
|
15 |
+
16,60,Caduceus_Embeddings.minus.inner_product,0.35198412698412695
|
16 |
+
17,50,Caduceus_Embeddings.minus.inner_product,0.13117323852617968
|
17 |
+
19,350,Caduceus_Embeddings.minus.inner_product,0.133932805756868
|
18 |
+
20,30,Caduceus_Embeddings.minus.inner_product,0.1227124183006536
|
19 |
+
22,20,Caduceus_Embeddings.minus.inner_product,0.08496732026143791
|
20 |
+
X,500,Caduceus_Embeddings.minus.inner_product,0.07633369589997713
|
mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Caduceus_Embeddings.plus.euclidean_distance.csv
ADDED
@@ -0,0 +1,20 @@
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,180,Caduceus_Embeddings.plus.euclidean_distance,0.14480931126519805
|
3 |
+
2,210,Caduceus_Embeddings.plus.euclidean_distance,0.20528089605086453
|
4 |
+
3,290,Caduceus_Embeddings.plus.euclidean_distance,0.14362561140650604
|
5 |
+
5,20,Caduceus_Embeddings.plus.euclidean_distance,0.22916666666666666
|
6 |
+
6,30,Caduceus_Embeddings.plus.euclidean_distance,0.2013888888888889
|
7 |
+
7,190,Caduceus_Embeddings.plus.euclidean_distance,0.1644567201941689
|
8 |
+
8,60,Caduceus_Embeddings.plus.euclidean_distance,0.09150495947171139
|
9 |
+
9,220,Caduceus_Embeddings.plus.euclidean_distance,0.09433480417476128
|
10 |
+
10,170,Caduceus_Embeddings.plus.euclidean_distance,0.08300458619128853
|
11 |
+
11,400,Caduceus_Embeddings.plus.euclidean_distance,0.11901308243349859
|
12 |
+
12,30,Caduceus_Embeddings.plus.euclidean_distance,0.10507936507936508
|
13 |
+
13,200,Caduceus_Embeddings.plus.euclidean_distance,0.07420904885916701
|
14 |
+
14,40,Caduceus_Embeddings.plus.euclidean_distance,0.18283991228070173
|
15 |
+
16,60,Caduceus_Embeddings.plus.euclidean_distance,0.1308390257898174
|
16 |
+
17,50,Caduceus_Embeddings.plus.euclidean_distance,0.23621166067974578
|
17 |
+
19,350,Caduceus_Embeddings.plus.euclidean_distance,0.1669825582841452
|
18 |
+
20,30,Caduceus_Embeddings.plus.euclidean_distance,0.1366013071895425
|
19 |
+
22,20,Caduceus_Embeddings.plus.euclidean_distance,0.31666666666666665
|
20 |
+
X,500,Caduceus_Embeddings.plus.euclidean_distance,0.12138311809686547
|
mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Enformer.LogisticRegression.chrom.subset_from_all.csv
ADDED
@@ -0,0 +1,20 @@
|
|
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|
|
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|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,180,Enformer.LogisticRegression.chrom.subset_from_all,0.27547675142521105
|
3 |
+
2,210,Enformer.LogisticRegression.chrom.subset_from_all,0.7031926276980454
|
4 |
+
3,290,Enformer.LogisticRegression.chrom.subset_from_all,0.3245377540090283
|
5 |
+
5,20,Enformer.LogisticRegression.chrom.subset_from_all,0.1125
|
6 |
+
6,30,Enformer.LogisticRegression.chrom.subset_from_all,0.5166666666666666
|
7 |
+
7,190,Enformer.LogisticRegression.chrom.subset_from_all,0.19961014632442528
|
8 |
+
8,60,Enformer.LogisticRegression.chrom.subset_from_all,0.23574103099965166
|
9 |
+
9,220,Enformer.LogisticRegression.chrom.subset_from_all,0.48003318064378625
|
10 |
+
10,170,Enformer.LogisticRegression.chrom.subset_from_all,0.34389667121473355
|
11 |
+
11,400,Enformer.LogisticRegression.chrom.subset_from_all,0.3121860065494301
|
12 |
+
12,30,Enformer.LogisticRegression.chrom.subset_from_all,0.7023809523809523
|
13 |
+
13,200,Enformer.LogisticRegression.chrom.subset_from_all,0.6368099022255975
|
14 |
+
14,40,Enformer.LogisticRegression.chrom.subset_from_all,0.11875
|
15 |
+
16,60,Enformer.LogisticRegression.chrom.subset_from_all,0.5937428111341154
|
16 |
+
17,50,Enformer.LogisticRegression.chrom.subset_from_all,0.32861102312321827
|
17 |
+
19,350,Enformer.LogisticRegression.chrom.subset_from_all,0.391111312995102
|
18 |
+
20,30,Enformer.LogisticRegression.chrom.subset_from_all,1.0
|
19 |
+
22,20,Enformer.LogisticRegression.chrom.subset_from_all,1.0
|
20 |
+
X,500,Enformer.LogisticRegression.chrom.subset_from_all,0.541780653574967
|
mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/Enformer_L2_L2.plus.all.csv
ADDED
@@ -0,0 +1,20 @@
|
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|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,180,Enformer_L2_L2.plus.all,0.2554444669312923
|
3 |
+
2,210,Enformer_L2_L2.plus.all,0.4715816646746082
|
4 |
+
3,290,Enformer_L2_L2.plus.all,0.3540146660075305
|
5 |
+
5,20,Enformer_L2_L2.plus.all,0.6111111111111112
|
6 |
+
6,30,Enformer_L2_L2.plus.all,0.38690476190476186
|
7 |
+
7,190,Enformer_L2_L2.plus.all,0.18794524293901857
|
8 |
+
8,60,Enformer_L2_L2.plus.all,0.4553157359761133
|
9 |
+
9,220,Enformer_L2_L2.plus.all,0.48145158513326336
|
10 |
+
10,170,Enformer_L2_L2.plus.all,0.26896707019508675
|
11 |
+
11,400,Enformer_L2_L2.plus.all,0.36573363629269234
|
12 |
+
12,30,Enformer_L2_L2.plus.all,0.6055555555555555
|
13 |
+
13,200,Enformer_L2_L2.plus.all,0.5521377824743748
|
14 |
+
14,40,Enformer_L2_L2.plus.all,0.09039638792928267
|
15 |
+
16,60,Enformer_L2_L2.plus.all,0.3745079830563701
|
16 |
+
17,50,Enformer_L2_L2.plus.all,0.13486772486772486
|
17 |
+
19,350,Enformer_L2_L2.plus.all,0.32935516161397815
|
18 |
+
20,30,Enformer_L2_L2.plus.all,0.8333333333333333
|
19 |
+
22,20,Enformer_L2_L2.plus.all,1.0
|
20 |
+
X,500,Enformer_L2_L2.plus.all,0.5899634261163853
|
mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/GPN-MSA.LogisticRegression.chrom.subset_from_all.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,180,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.33206916275044523
|
3 |
+
2,210,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.9344860565790798
|
4 |
+
3,290,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.8647576223525206
|
5 |
+
5,20,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.3269230769230769
|
6 |
+
6,30,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.8666666666666667
|
7 |
+
7,190,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.9232087099347157
|
8 |
+
8,60,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.5756854256854257
|
9 |
+
9,220,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.8957781723447131
|
10 |
+
10,170,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.5153466657792741
|
11 |
+
11,400,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.5321414869609583
|
12 |
+
12,30,GPN-MSA.LogisticRegression.chrom.subset_from_all,1.0
|
13 |
+
13,200,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.5073882965238709
|
14 |
+
14,40,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.24486714975845408
|
15 |
+
16,60,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.8583333333333334
|
16 |
+
17,50,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.7227272727272727
|
17 |
+
19,350,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.9382757335366151
|
18 |
+
20,30,GPN-MSA.LogisticRegression.chrom.subset_from_all,1.0
|
19 |
+
22,20,GPN-MSA.LogisticRegression.chrom.subset_from_all,1.0
|
20 |
+
X,500,GPN-MSA.LogisticRegression.chrom.subset_from_all,0.4439748737944069
|
mendelian_traits_matched_9/AUPRC_by_chrom/no_cadd_overlap/GPN-MSA_LLR.minus.score.csv
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
chrom,n,Model,AUPRC
|
2 |
+
1,180,GPN-MSA_LLR.minus.score,0.3612766240160113
|
3 |
+
2,210,GPN-MSA_LLR.minus.score,0.8813550513880595
|
4 |
+
3,290,GPN-MSA_LLR.minus.score,0.7610265478043932
|
5 |
+
5,20,GPN-MSA_LLR.minus.score,0.34090909090909094
|
6 |
+
6,30,GPN-MSA_LLR.minus.score,0.1865079365079365
|
7 |
+
7,190,GPN-MSA_LLR.minus.score,0.8833184404134271
|
8 |
+
8,60,GPN-MSA_LLR.minus.score,0.6436097427476737
|
9 |
+
9,220,GPN-MSA_LLR.minus.score,0.7403465242812366
|
10 |
+
10,170,GPN-MSA_LLR.minus.score,0.3806155539665536
|
11 |
+
11,400,GPN-MSA_LLR.minus.score,0.6213070778284594
|
12 |
+
12,30,GPN-MSA_LLR.minus.score,1.0
|
13 |
+
13,200,GPN-MSA_LLR.minus.score,0.6688209802270113
|
14 |
+
14,40,GPN-MSA_LLR.minus.score,0.1853354978354978
|
15 |
+
16,60,GPN-MSA_LLR.minus.score,0.547069597069597
|
16 |
+
17,50,GPN-MSA_LLR.minus.score,0.6559649122807018
|
17 |
+
19,350,GPN-MSA_LLR.minus.score,0.9082953757647307
|
18 |
+
20,30,GPN-MSA_LLR.minus.score,0.8666666666666667
|
19 |
+
22,20,GPN-MSA_LLR.minus.score,0.7
|
20 |
+
X,500,GPN-MSA_LLR.minus.score,0.6531952615307103
|