cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14676935
title: Additional file 6 of Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing

description: Additional file 6: Table S5. Dataset 1 false discovery rate (FDR) q-values for differential abundance methods when performed on filtered data. Dataset 1 FDR q-values for all differential abundance methods were aggregated into one table along with the mean relative abundance of each genus for PD patients (Case MRA) and control subjects (Control MRA) and the mean relative abundance ratio of Case MRA to Control MRA (MRAR). 201 PD patients and 132 controls were included in all analyses. Genera detected in at least 10% of samples (133 genera) were included in the analyses. If an analysis resulted in an "NA" for a result, or a result was not outputted by the method, a 1 was placed for the FDR q-value. Calculations for the number of detected DA signatures for each method are located at the bottom of the table. Calculations for the number of methods that detected or replicated a genus as differentially abundant are located to the right of the table.
DOI: 10.6084/m9.figshare.14676920.v1
title: Additional file 1 of Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing

description: Additional file 1. Results for t-tests when testing for differences between datasets for various metrics.
DOI: 10.6084/m9.figshare.14676935.v1
title: Additional file 6 of Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing

description: Additional file 6: Table S5. Dataset 1 false discovery rate (FDR) q-values for differential abundance methods when performed on filtered data. Dataset 1 FDR q-values for all differential abundance methods were aggregated into one table along with the mean relative abundance of each genus for PD patients (Case MRA) and control subjects (Control MRA) and the mean relative abundance ratio of Case MRA to Control MRA (MRAR). 201 PD patients and 132 controls were included in all analyses. Genera detected in at least 10% of samples (133 genera) were included in the analyses. If an analysis resulted in an "NA" for a result, or a result was not outputted by the method, a 1 was placed for the FDR q-value. Calculations for the number of detected DA signatures for each method are located at the bottom of the table. Calculations for the number of methods that detected or replicated a genus as differentially abundant are located to the right of the table.
DOI: 10.6084/m9.figshare.14676938
title: Additional file 7 of Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing

description: Additional file 7: Table S6. Dataset 2 false discovery rate (FDR) q-values for differential abundance methods when performed on filtered data. Dataset 2 FDR q-values for all differential abundance methods were aggregated into one table along with the mean relative abundance of each genus for PD patients (Case MRA) and control subjects (Control MRA) and the mean relative abundance ratio of Case MRA to Control MRA (MRAR). 323 PD patients and 184 controls were included in all analyses. Genera detected in at least 10% of samples (195 genera) were included in the analyses. If an analysis resulted in an "NA" for a result, or a result was not outputted by the method, a 1 was placed for the FDR q-value. Calculations for the number of detected DA signatures for each method are located at the bottom of the table. Calculations for the number of methods that detected or replicated a genus as differentially abundant are located to the right of the table.
DOI: 10.6084/m9.figshare.14676929.v1
title: Additional file 4 of Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing

description: Additional file 4: Table S3. Dataset 1 false discovery rate (FDR) q-values for differential abundance methods when performed on unfiltered data. Dataset 1 FDR q-values for all differential abundance methods were aggregated into one table along with the mean relative abundance of each genus for PD patients (Case MRA) and control subjects (Control MRA) and the mean relative abundance ratio of Case MRA to Control MRA (MRAR). 201 PD patients and 132 controls were included in all analyses. All genera detected in dataset 1 (445 genera) were included in the analyses. If an analysis resulted in an "NA" for a result, or a result was not outputted by the method, a 1 was placed for the FDR q-value. Calculations for the number of detected DA signatures for each method are located at the bottom of the table. Calculations for the number of methods that detected or replicated a genus as differentially abundant are located to the right of the table.
DOI: 10.6084/m9.figshare.14676941
title: Additional file 8 of Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing

description: Additional file 8: Table S7. Pairwise concordances between methods with summary statistics calculations. Differential abundance testing was performed using 23 methods on both unfiltered (A-C, 445 genera dataset1, 561 genera dataset 2), and filtered (D-F, 133 genera dataset 1, 195 genera dataset 2) taxonomic data. Values in heatmap cells are pairwise concordances of differential abundance signature calls between two methods. Concordances within each dataset (A,B,D,E) were calculated by first creating a binary taxa by method matrix denoting which methods did (value of 1) or did not (value of 0) detect a certain differential abundance signature, then between each pair of methods, calculating the proportion of detected differential abundance signatures in common out of the total detected between the two methods. Calculation of concordances for replicated differential abundance signatures (C,F) were calculated by first creating a binary taxa by method matrix that denoted whether a signature was replicated (multiple testing corrected significant and same case:control mean relative abundance ratio in both datasets) across datasets (value of 1), or was not replicated (value of 0), then between each pair of methods, calculating the proportion of replicated signatures in common out of the total replicated between the two methods. Cells are colored by a blue (lower concordance) to white (around the mean pairwise concordance of each heatmap) to orange (higher concordance) color gradient. Methods are ordered from lowest (bottom, left) to highest (top, right) mean pairwise concordance. SAMseq did not successfully run for dataset 2 unfiltered data, therefore, table values for SAMseq have been put as "NA" and colored grey in B and C. KW: Kruskal-Wallis; GLM: generalized linear model; CLR: centered log-ratio transformation; TSS: total sum scaling; rCLR: robust CLR with matrix completion using OptSpace algorithm; TMM: trimmed mean of M-values; GLM NBZI: generalized linear model assuming negative binomial distribution with, or without, zero-inflation; RLE: relative log expression.
DOI: 10.6084/m9.figshare.14676941.v1
title: Additional file 8 of Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing

description: Additional file 8: Table S7. Pairwise concordances between methods with summary statistics calculations. Differential abundance testing was performed using 23 methods on both unfiltered (A-C, 445 genera dataset1, 561 genera dataset 2), and filtered (D-F, 133 genera dataset 1, 195 genera dataset 2) taxonomic data. Values in heatmap cells are pairwise concordances of differential abundance signature calls between two methods. Concordances within each dataset (A,B,D,E) were calculated by first creating a binary taxa by method matrix denoting which methods did (value of 1) or did not (value of 0) detect a certain differential abundance signature, then between each pair of methods, calculating the proportion of detected differential abundance signatures in common out of the total detected between the two methods. Calculation of concordances for replicated differential abundance signatures (C,F) were calculated by first creating a binary taxa by method matrix that denoted whether a signature was replicated (multiple testing corrected significant and same case:control mean relative abundance ratio in both datasets) across datasets (value of 1), or was not replicated (value of 0), then between each pair of methods, calculating the proportion of replicated signatures in common out of the total replicated between the two methods. Cells are colored by a blue (lower concordance) to white (around the mean pairwise concordance of each heatmap) to orange (higher concordance) color gradient. Methods are ordered from lowest (bottom, left) to highest (top, right) mean pairwise concordance. SAMseq did not successfully run for dataset 2 unfiltered data, therefore, table values for SAMseq have been put as "NA" and colored grey in B and C. KW: Kruskal-Wallis; GLM: generalized linear model; CLR: centered log-ratio transformation; TSS: total sum scaling; rCLR: robust CLR with matrix completion using OptSpace algorithm; TMM: trimmed mean of M-values; GLM NBZI: generalized linear model assuming negative binomial distribution with, or without, zero-inflation; RLE: relative log expression.
DOI: 10.6084/m9.figshare.14676929
title: Additional file 4 of Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing

description: Additional file 4: Table S3. Dataset 1 false discovery rate (FDR) q-values for differential abundance methods when performed on unfiltered data. Dataset 1 FDR q-values for all differential abundance methods were aggregated into one table along with the mean relative abundance of each genus for PD patients (Case MRA) and control subjects (Control MRA) and the mean relative abundance ratio of Case MRA to Control MRA (MRAR). 201 PD patients and 132 controls were included in all analyses. All genera detected in dataset 1 (445 genera) were included in the analyses. If an analysis resulted in an "NA" for a result, or a result was not outputted by the method, a 1 was placed for the FDR q-value. Calculations for the number of detected DA signatures for each method are located at the bottom of the table. Calculations for the number of methods that detected or replicated a genus as differentially abundant are located to the right of the table.
DOI: 10.6084/m9.figshare.14676944
title: Additional file 9 of Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing

description: Additional file 9: Table S8. Table further describing heatmap in Fig 4. A table was created to mirror the heatmap in Fig 4 in order to further describe the values being represented in the heatmap visualization and calculate number of methods replicating a particular DA signature. Table rows and columns are ordered to match Fig 4. Values for mean relative abundance ratios and mean relative abundances of each taxon in dataset 1 (MRAR_1 and MRA_1) and dataset 2 (MRAR_2 and MRA_2) from the heatmap in Fig 4 are shown. For each method column, cells are labeled to show what DA signature replicated ("Replicated") or did not replicate ("-") instead of the actual values used for generating the heatmap (1 and 0 respectively). Calculations for the number of methods a DA signature was replicated by are located at the right most column of the table. Only taxa that had at least 1 method replicate it's DA signature are included in the table. Heatmap and hierarchical clustering is based on method results when performed on filtered data (excluding taxa found in &lt; 10% of samples). KW: Kruskal-Wallis; GLM: generalized linear model; CLR: centered log-ratio transformation; TSS: total sum scaling; rCLR: robust CLR with matrix completion using OptSpace algorithm; TMM: trimmed mean of M-values; GLM NBZI: generalized linear model assuming negative binomial distribution with, or without, zero-inflation; RLE: relative log expression.
DOI: 10.6084/m9.figshare.14676944.v1
title: Additional file 9 of Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing

description: Additional file 9: Table S8. Table further describing heatmap in Fig 4. A table was created to mirror the heatmap in Fig 4 in order to further describe the values being represented in the heatmap visualization and calculate number of methods replicating a particular DA signature. Table rows and columns are ordered to match Fig 4. Values for mean relative abundance ratios and mean relative abundances of each taxon in dataset 1 (MRAR_1 and MRA_1) and dataset 2 (MRAR_2 and MRA_2) from the heatmap in Fig 4 are shown. For each method column, cells are labeled to show what DA signature replicated ("Replicated") or did not replicate ("-") instead of the actual values used for generating the heatmap (1 and 0 respectively). Calculations for the number of methods a DA signature was replicated by are located at the right most column of the table. Only taxa that had at least 1 method replicate it's DA signature are included in the table. Heatmap and hierarchical clustering is based on method results when performed on filtered data (excluding taxa found in &lt; 10% of samples). KW: Kruskal-Wallis; GLM: generalized linear model; CLR: centered log-ratio transformation; TSS: total sum scaling; rCLR: robust CLR with matrix completion using OptSpace algorithm; TMM: trimmed mean of M-values; GLM NBZI: generalized linear model assuming negative binomial distribution with, or without, zero-inflation; RLE: relative log expression.
DOI: 10.6084/m9.figshare.14676938.v1
title: Additional file 7 of Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing

description: Additional file 7: Table S6. Dataset 2 false discovery rate (FDR) q-values for differential abundance methods when performed on filtered data. Dataset 2 FDR q-values for all differential abundance methods were aggregated into one table along with the mean relative abundance of each genus for PD patients (Case MRA) and control subjects (Control MRA) and the mean relative abundance ratio of Case MRA to Control MRA (MRAR). 323 PD patients and 184 controls were included in all analyses. Genera detected in at least 10% of samples (195 genera) were included in the analyses. If an analysis resulted in an "NA" for a result, or a result was not outputted by the method, a 1 was placed for the FDR q-value. Calculations for the number of detected DA signatures for each method are located at the bottom of the table. Calculations for the number of methods that detected or replicated a genus as differentially abundant are located to the right of the table.
DOI: 10.6084/m9.figshare.14676950.v1
title: Additional file 1 of Clinical and epigenetic features of colorectal cancer patients with somatic POLE proofreading mutations

description: Additional file 1. Table 1. Detailed information of 65 MSI CRC patients.
DOI: 10.6084/m9.figshare.14676953
title: Additional file 2 of Clinical and epigenetic features of colorectal cancer patients with somatic POLE proofreading mutations

description: Additional file 2. Table 2. Primer sequences.
DOI: 10.6084/m9.figshare.14676953.v1
title: Additional file 2 of Clinical and epigenetic features of colorectal cancer patients with somatic POLE proofreading mutations

description: Additional file 2. Table 2. Primer sequences.
DOI: 10.6084/m9.figshare.14676950
title: Additional file 1 of Clinical and epigenetic features of colorectal cancer patients with somatic POLE proofreading mutations

description: Additional file 1. Table 1. Detailed information of 65 MSI CRC patients.
DOI: 10.6084/m9.figshare.14527695.v1
title: Additional file 1 of Genome-wide association study of micronaire using a natural population of representative upland cotton (Gossypium hirsutum L.)

description: Additional file 1: Table S1. Analysis of variance for FM.
DOI: 10.6084/m9.figshare.14527701
title: Additional file 2 of Genome-wide association study of micronaire using a natural population of representative upland cotton (Gossypium hirsutum L.)

description: Additional file 2: Fig. S1. Box plots of fiber micronaire in upland cotton accessions in different environments. Fig. S2. QQ plots against genotypic and phenotypic data represent the normal distribution for genotypic and phenotypic data. The lowercase letters a, b, and c represent the QQ plots in Anyang in 2014, 2015 and 2016, respectively; the letters d and e represent the QQ plots in Aral and Sanya in 2016, respectively; and f represents the QQ plots for BLUP.
DOI: 10.6084/m9.figshare.14527701.v1
title: Additional file 2 of Genome-wide association study of micronaire using a natural population of representative upland cotton (Gossypium hirsutum L.)

description: Additional file 2: Fig. S1. Box plots of fiber micronaire in upland cotton accessions in different environments. Fig. S2. QQ plots against genotypic and phenotypic data represent the normal distribution for genotypic and phenotypic data. The lowercase letters a, b, and c represent the QQ plots in Anyang in 2014, 2015 and 2016, respectively; the letters d and e represent the QQ plots in Aral and Sanya in 2016, respectively; and f represents the QQ plots for BLUP.
DOI: 10.6084/m9.figshare.14527695
title: Additional file 1 of Genome-wide association study of micronaire using a natural population of representative upland cotton (Gossypium hirsutum L.)

description: Additional file 1: Table S1. Analysis of variance for FM.
DOI: 10.6084/m9.figshare.14676982
title: Additional file 2 of Comparative evaluation of full-length isoform quantification from RNA-Seq

description: Additional file 2. Supplemental Tables
DOI: 10.6084/m9.figshare.14676982.v1
title: Additional file 2 of Comparative evaluation of full-length isoform quantification from RNA-Seq

description: Additional file 2. Supplemental Tables
DOI: 10.6084/m9.figshare.14676994
title: Additional file 2 of Psychosomatic symptoms questionnaire (PSQ-39): a psychometric study among general population of Iranian adults

description: Additional file 2:.
DOI: 10.6084/m9.figshare.14676997
title: Additional file 3 of Psychosomatic symptoms questionnaire (PSQ-39): a psychometric study among general population of Iranian adults

description: Additional file 3:.
DOI: 10.6084/m9.figshare.14676997.v1
title: Additional file 3 of Psychosomatic symptoms questionnaire (PSQ-39): a psychometric study among general population of Iranian adults

description: Additional file 3:.
DOI: 10.6084/m9.figshare.14676994.v1
title: Additional file 2 of Psychosomatic symptoms questionnaire (PSQ-39): a psychometric study among general population of Iranian adults

description: Additional file 2:.
DOI: 10.6084/m9.figshare.14677018
title: Additional file 1 of Prenatal treatment with rapamycin restores enhanced hippocampal mGluR-LTD and mushroom spine size in a Down’s syndrome mouse model

description: Additional file 1: Table S1. List of proteins detected by tandem mass spectrometry iTRAQ in technical duplicates of WT and Ts1Cje synaptoneurosomes (SNs). Quantification is referred to one of the WT samples. Table S2. Same data as in Table S1 after elimination of proteins identified by only one unique peptide. Table S3. Geometric mean of the relative protein amount in Ts1Cje SNs, after elimination from Table S2 of proteins not detected in all the samples, as well as technical replicates with CV% &gt; 30%. Table S4. Complete hierarchy of PANTHER Go-Slim Cellular Component proteins overrepresented and underrepresented in WT and Ts1Cje SNs.
DOI: 10.6084/m9.figshare.14677018.v1
title: Additional file 1 of Prenatal treatment with rapamycin restores enhanced hippocampal mGluR-LTD and mushroom spine size in a Down’s syndrome mouse model

description: Additional file 1: Table S1. List of proteins detected by tandem mass spectrometry iTRAQ in technical duplicates of WT and Ts1Cje synaptoneurosomes (SNs). Quantification is referred to one of the WT samples. Table S2. Same data as in Table S1 after elimination of proteins identified by only one unique peptide. Table S3. Geometric mean of the relative protein amount in Ts1Cje SNs, after elimination from Table S2 of proteins not detected in all the samples, as well as technical replicates with CV% &gt; 30%. Table S4. Complete hierarchy of PANTHER Go-Slim Cellular Component proteins overrepresented and underrepresented in WT and Ts1Cje SNs.
DOI: 10.6084/m9.figshare.14677021
title: Additional file 2 of Prenatal treatment with rapamycin restores enhanced hippocampal mGluR-LTD and mushroom spine size in a Down’s syndrome mouse model

description: Additional file 2: Table S5. List of proteins affected in Ts1Cje SNs. Table S6. List of canonical pathways affected in Ts1Cje SNs. Table S7. Z-score analysis of canonical pathways in Ts1Cje SNs.
DOI: 10.6084/m9.figshare.14677021.v1
title: Additional file 2 of Prenatal treatment with rapamycin restores enhanced hippocampal mGluR-LTD and mushroom spine size in a Down’s syndrome mouse model

description: Additional file 2: Table S5. List of proteins affected in Ts1Cje SNs. Table S6. List of canonical pathways affected in Ts1Cje SNs. Table S7. Z-score analysis of canonical pathways in Ts1Cje SNs.
DOI: 10.6084/m9.figshare.14677024.v1
title: Additional file 3 of Prenatal treatment with rapamycin restores enhanced hippocampal mGluR-LTD and mushroom spine size in a Down’s syndrome mouse model

description: Additional file 3: Table S8. Number of spines belonging to each category (size) included in Fig. 6.
DOI: 10.6084/m9.figshare.14677024
title: Additional file 3 of Prenatal treatment with rapamycin restores enhanced hippocampal mGluR-LTD and mushroom spine size in a Down’s syndrome mouse model

description: Additional file 3: Table S8. Number of spines belonging to each category (size) included in Fig. 6.
DOI: 10.6084/m9.figshare.14677027
title: Additional file 1 of Blood DNA methylation and COVID-19 outcomes

description: Additional file 1. Descriptions of COVID-19 related DMRs.
DOI: 10.6084/m9.figshare.14677027.v1
title: Additional file 1 of Blood DNA methylation and COVID-19 outcomes

description: Additional file 1. Descriptions of COVID-19 related DMRs.
DOI: 10.6084/m9.figshare.14677040
title: Additional file 2 of Samplot: a platform for structural variant visual validation and automated filtering

description: Additional file 2: Supplementary Table 1. SV calling statistics organized by sample, SV caller, and filtering method.
DOI: 10.6084/m9.figshare.14677043
title: Additional file 3 of Samplot: a platform for structural variant visual validation and automated filtering

description: Additional file 3: Supplementary Table 2. Statistics for CHM1/CHM13 allele balance mixture experiment.
DOI: 10.6084/m9.figshare.14677046
title: Additional file 4 of Samplot: a platform for structural variant visual validation and automated filtering

description: Additional file 4: Supplementary Table 3. Links for sequence and alignment file data.
DOI: 10.6084/m9.figshare.14677046.v1
title: Additional file 4 of Samplot: a platform for structural variant visual validation and automated filtering

description: Additional file 4: Supplementary Table 3. Links for sequence and alignment file data.
DOI: 10.6084/m9.figshare.14677049.v1
title: Additional file 5 of Samplot: a platform for structural variant visual validation and automated filtering

description: Additional file 5: Supplementary Table 4. Links for VCF file data.