cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10212116
title: ecDNA machine learning modeling

description: 1. ecDNA_cargo_gene_modeling_data.csv.gz
The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes.
library(data.table)
data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds")
colnames(data)[3] = "total_cn"
data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",")

 
2. gcap_pcawg_WGS_result.tar.gz
GCAP analysis results for PCAWG allele-specific copy number profiles derived from WGS.
 
3. gcap_tcga_snp6_result.tar.gz
GCAP analysis results for TCGA allele-specific copy number profiles derived from SNP6 array.
 
4. gcap_Changkang_WES_result.tar.gz
GCAP analysis results for SYSUCC Changkang allele-specific copy number profiles derived from tumor-normal paired WES.
 
5. tcga_overlap_gene_wgs.rds, tcga_overlap_gene_snp.rds and tcga_overlap_gene_wes.rds
These datasets contain TCGA gene-level copy number results in R data format from overlapping samples (dataset above). WGS from PCAWG, SNP array, and WES from GDC portal.
 
6. cellline-batch1.zip & cellline-batch1.zip
 
GCAP results of cell line batch 1 and batch 2.
 
7. AA_cellline_wgs.zip
AA software results for cell line batch 1.
 
8. Batch2_AA_summary.xlsx
AA software results for cell line batch 2.
 
9. FISH-for-supp-file.zip
Extended raw FISH images from 12 CRC samples.
 
10. SNU216.zip
Extended AA and GCAP analysis on SNU216.
 
11. aa_ffpe.zip and AA_summary_table_of_6_erbb2_ffpe_samples.xlsx
Extended AA running files (all results) and result summary data for 6 GCAP predicted ERBB2 amp clinical samples.
DOI: 10.5281/zenodo.10377195
title: ecDNA machine learning modeling

description: 1. ecDNA_cargo_gene_modeling_data.csv.gz

The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes.

library(data.table) data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds") colnames(data)[3] = "total_cn" data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",")

 

2. gcap_pcawg_WGS_result.tar.gz

GCAP analysis results for PCAWG allele-specific copy number profiles derived from WGS.

 

3. gcap_tcga_snp6_result.tar.gz

GCAP analysis results for TCGA allele-specific copy number profiles derived from SNP6 array.

 

4. gcap_Changkang_WES_result.tar.gz

GCAP analysis results for SYSUCC Changkang allele-specific copy number profiles derived from tumor-normal paired WES.

 

5. tcga_overlap_gene_wgs.rds, tcga_overlap_gene_snp.rds and tcga_overlap_gene_wes.rds

These datasets contain TCGA gene-level copy number results in R data format from overlapping samples (dataset above). WGS from PCAWG, SNP array, and WES from GDC portal.

 

6. cellline-batch1.zip & cellline-batch1.zip

 

GCAP results of cell line batch 1 and batch 2.

 

7. AA_cellline_wgs.zip

AA software results for cell line batch 1.

 

8. Batch2_AA_summary.xlsx

AA software results for cell line batch 2.

 

9. FISH-for-supp-file.zip

Extended raw FISH images from 12 CRC samples.

 

10. SNU216.zip

Extended AA and GCAP analysis on SNU216.

 

11. aa_ffpe.zip and AA_summary_table_of_6_erbb2_ffpe_samples.xlsx

Extended AA running files (all results) and result summary data for 6 GCAP predicted ERBB2 amp clinical samples.

 

12. source data of fig.4
DOI: 10.5281/zenodo.10388940
title: ecDNA machine learning modeling

description: 1. ecDNA_cargo_gene_modeling_data.csv.gz

The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes.

library(data.table) data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds") colnames(data)[3] = "total_cn" data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",")

 

2. gcap_pcawg_WGS_result.tar.gz

GCAP analysis results for PCAWG allele-specific copy number profiles derived from WGS.

 

3. gcap_tcga_snp6_result.tar.gz

GCAP analysis results for TCGA allele-specific copy number profiles derived from SNP6 array.

 

4. gcap_Changkang_WES_result.tar.gz

GCAP analysis results for SYSUCC Changkang allele-specific copy number profiles derived from tumor-normal paired WES.

 

5. tcga_overlap_gene_wgs.rds, tcga_overlap_gene_snp.rds and tcga_overlap_gene_wes.rds

These datasets contain TCGA gene-level copy number results in R data format from overlapping samples (dataset above). WGS from PCAWG, SNP array, and WES from GDC portal.

 

6. cellline-batch1.zip & cellline-batch1.zip

 

GCAP results of cell line batch 1 and batch 2.

 

7. AA_cellline_wgs.zip

AA software results for cell line batch 1.

 

8. Batch2_AA_summary.xlsx

AA software results for cell line batch 2.

 

9. FISH-for-supp-file.zip

Extended raw FISH images from 12 CRC samples.

 

10. SNU216.zip

Extended AA and GCAP analysis on SNU216.

 

11. aa_ffpe.zip and AA_summary_table_of_6_erbb2_ffpe_samples.xlsx

Extended AA running files (all results) and result summary data for 6 GCAP predicted ERBB2 amp clinical samples.

 

12. source data of fig.4

 

13. source data of supp fig.2 subplots
DOI: 10.5281/zenodo.10389804
title: ecDNA machine learning modeling

description: 1. ecDNA_cargo_gene_modeling_data.csv.gz

The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes.

library(data.table) data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds") colnames(data)[3] = "total_cn" data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",")

 

2. gcap_pcawg_WGS_result.tar.gz

GCAP analysis results for PCAWG allele-specific copy number profiles derived from WGS.

 

3. gcap_tcga_snp6_result.tar.gz

GCAP analysis results for TCGA allele-specific copy number profiles derived from SNP6 array.

 

4. gcap_Changkang_WES_result.tar.gz

GCAP analysis results for SYSUCC Changkang allele-specific copy number profiles derived from tumor-normal paired WES.

 

5. tcga_overlap_gene_wgs.rds, tcga_overlap_gene_snp.rds and tcga_overlap_gene_wes.rds

These datasets contain TCGA gene-level copy number results in R data format from overlapping samples (dataset above). WGS from PCAWG, SNP array, and WES from GDC portal.

 

6. cellline-batch1.zip & cellline-batch1.zip

 

GCAP results of cell line batch 1 and batch 2.

 

7. AA_cellline_wgs.zip

AA software results for cell line batch 1.

 

8. Batch2_AA_summary.xlsx

AA software results for cell line batch 2.

 

9. FISH-for-supp-file.zip

Extended raw FISH images from 12 CRC samples.

 

10. SNU216.zip

Extended AA and GCAP analysis on SNU216.

 

11. aa_ffpe.zip and AA_summary_table_of_6_erbb2_ffpe_samples.xlsx

Extended AA running files (all results) and result summary data for 6 GCAP predicted ERBB2 amp clinical samples.

 

12. source data of fig.4

 

13. source data of supp fig.2 subplots

 

13. source data of supp fig.15

 

14. GCAP result data objects for three ICB cohorts. Both gene-level and sample-level data included.
DOI: 10.5281/zenodo.10472659
title: ecDNA machine learning modeling

description: 1. ecDNA_cargo_gene_modeling_data.csv.gz

The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes.

library(data.table)

data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds")

colnames(data)[3] = "total_cn"

data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",")

 

2. gcap_pcawg_WGS_result.tar.gz

GCAP analysis results for PCAWG allele-specific copy number profiles derived from WGS.

 

3. gcap_tcga_snp6_result.tar.gz

GCAP analysis results for TCGA allele-specific copy number profiles derived from SNP6 array.

 

4. gcap_Changkang_WES_result.tar.gz

GCAP analysis results for SYSUCC Changkang allele-specific copy number profiles derived from tumor-normal paired WES.

 

5. tcga_overlap_gene_wgs.rds, tcga_overlap_gene_snp.rds and tcga_overlap_gene_wes.rds

These datasets contain TCGA gene-level copy number results in R data format from overlapping samples (dataset above). WGS from PCAWG, SNP array, and WES from GDC portal.

 

6. cellline-batch1.zip & cellline-batch1.zip

 

GCAP results of cell line batch 1 and batch 2.

 

7. AA_cellline_wgs.zip

AA software results for cell line batch 1.

 

8. Batch2_AA_summary.xlsx

AA software results for cell line batch 2.

 

9. FISH-for-supp-file.zip

Extended raw FISH images from 12 CRC samples.

 

10. SNU216.zip

Extended AA and GCAP analysis on SNU216.

 

11. aa_ffpe.zip and AA_summary_table_of_6_erbb2_ffpe_samples.xlsx

Extended AA running files (all results) and result summary data for 6 GCAP predicted ERBB2 amp clinical samples.

 

12. source data of fig.4

 

13. source data of supp fig.2 subplots

 

13. source data of supp fig.15

 

14. GCAP result data objects for three ICB cohorts. Both gene-level and sample-level data included.

 

15. PDX-P68: processed (AA and CNV) data of P68 from WGS and WES data.
DOI: 10.5281/zenodo.11082530
title: ecDNA machine learning modeling
title: The source data of supplementary figure 13 in the accompanying article table has been found to have issues, which were identified as a result of improper Excel operation. Here, we have uploaded the correct data table

description: The source data of supplementary figure 13 in the accompanying article table has been found to have issues, which were identified as a result of improper Excel operation. Here, we have uploaded the correct data table

 

1. ecDNA_cargo_gene_modeling_data.csv.gz

The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes.

library(data.table)

data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds")

colnames(data)[3] = "total_cn"

data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",")

 

2. gcap_pcawg_WGS_result.tar.gz

GCAP analysis results for PCAWG allele-specific copy number profiles derived from WGS.

 

3. gcap_tcga_snp6_result.tar.gz

GCAP analysis results for TCGA allele-specific copy number profiles derived from SNP6 array.

 

4. gcap_Changkang_WES_result.tar.gz

GCAP analysis results for SYSUCC Changkang allele-specific copy number profiles derived from tumor-normal paired WES.

 

5. tcga_overlap_gene_wgs.rds, tcga_overlap_gene_snp.rds and tcga_overlap_gene_wes.rds

These datasets contain TCGA gene-level copy number results in R data format from overlapping samples (dataset above). WGS from PCAWG, SNP array, and WES from GDC portal.

 

6. cellline-batch1.zip & cellline-batch1.zip

 

GCAP results of cell line batch 1 and batch 2.

 

7. AA_cellline_wgs.zip

AA software results for cell line batch 1.

 

8. Batch2_AA_summary.xlsx

AA software results for cell line batch 2.

 

9. FISH-for-supp-file.zip

Extended raw FISH images from 12 CRC samples.

 

10. SNU216.zip

Extended AA and GCAP analysis on SNU216.

 

11. aa_ffpe.zip and AA_summary_table_of_6_erbb2_ffpe_samples.xlsx

Extended AA running files (all results) and result summary data for 6 GCAP predicted ERBB2 amp clinical samples.

 

12. source data of fig.4

 

13. source data of supp fig.2 subplots

 

13. source data of supp fig.15

 

14. GCAP result data objects for three ICB cohorts. Both gene-level and sample-level data included.

 

15. PDX-P68: processed (AA and CNV) data of P68 from WGS and WES data.

 

16. source data of supp fig.13
DOI: 10.5281/zenodo.12561157
title: ecDNA machine learning modeling
title: The source data of supplementary figure 13 in the accompanying article table has been found to have issues, which were identified as a result of improper Excel operation. Here, we have uploaded the correct data table

description: 1. Today (2024-06-27), we discovered an issue with the labeling of sample groups in one of the supplementary figures (Supplementary Figure 14c) in our published article. We have corrected the figure and present it here, and we extend our apologies to all readers for any confusion this may have caused (although no report received).

2. The source data of supplementary figure 13 in the accompanying article table has been found to have issues, which were identified as a result of improper Excel operation. Here, we have uploaded the correct data table

--------------------------------------------------

 

1. ecDNA_cargo_gene_modeling_data.csv.gz

The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes.

library(data.table)

data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds")

colnames(data)[3] = "total_cn"

data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",")

 

2. gcap_pcawg_WGS_result.tar.gz

GCAP analysis results for PCAWG allele-specific copy number profiles derived from WGS.

 

3. gcap_tcga_snp6_result.tar.gz

GCAP analysis results for TCGA allele-specific copy number profiles derived from SNP6 array.

 

4. gcap_Changkang_WES_result.tar.gz

GCAP analysis results for SYSUCC Changkang allele-specific copy number profiles derived from tumor-normal paired WES.

 

5. tcga_overlap_gene_wgs.rds, tcga_overlap_gene_snp.rds and tcga_overlap_gene_wes.rds

These datasets contain TCGA gene-level copy number results in R data format from overlapping samples (dataset above). WGS from PCAWG, SNP array, and WES from GDC portal.

 

6. cellline-batch1.zip & cellline-batch1.zip

 

GCAP results of cell line batch 1 and batch 2.

 

7. AA_cellline_wgs.zip

AA software results for cell line batch 1.

 

8. Batch2_AA_summary.xlsx

AA software results for cell line batch 2.

 

9. FISH-for-supp-file.zip

Extended raw FISH images from 12 CRC samples.

 

10. SNU216.zip

Extended AA and GCAP analysis on SNU216.

 

11. aa_ffpe.zip and AA_summary_table_of_6_erbb2_ffpe_samples.xlsx

Extended AA running files (all results) and result summary data for 6 GCAP predicted ERBB2 amp clinical samples.

 

12. source data of fig.4

 

13. source data of supp fig.2 subplots

 

13. source data of supp fig.15

 

14. GCAP result data objects for three ICB cohorts. Both gene-level and sample-level data included.

 

15. PDX-P68: processed (AA and CNV) data of P68 from WGS and WES data.

 

16. source data of supp fig.13

 

17. updated supplementary figure 14
DOI: 10.5281/zenodo.15580781
title: ecDNA machine learning modeling
title: The source data of supplementary figure 13 in the accompanying article table has been found to have issues, which were identified as a result of improper Excel operation. Here, we have uploaded the correct data table

description: 1. Today (2024-06-27), we discovered an issue with the labeling of sample groups in one of the supplementary figures (Supplementary Figure 14c) in our published article. We have corrected the figure and present it here, and we extend our apologies to all readers for any confusion this may have caused (although no report received).

2. The source data of supplementary figure 13 in the accompanying article table has been found to have issues, which were identified as a result of improper Excel operation. Here, we have uploaded the correct data table

--------------------------------------------------

 

1. ecDNA_cargo_gene_modeling_data.csv.gz

The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes.

library(data.table)

data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds")

colnames(data)[3] = "total_cn"

data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",")

 

2. gcap_pcawg_WGS_result.tar.gz

GCAP analysis results for PCAWG allele-specific copy number profiles derived from WGS.

 

3. gcap_tcga_snp6_result.tar.gz

GCAP analysis results for TCGA allele-specific copy number profiles derived from SNP6 array.

 

4. gcap_Changkang_WES_result.tar.gz

GCAP analysis results for SYSUCC Changkang allele-specific copy number profiles derived from tumor-normal paired WES.

 

5. tcga_overlap_gene_wgs.rds, tcga_overlap_gene_snp.rds and tcga_overlap_gene_wes.rds

These datasets contain TCGA gene-level copy number results in R data format from overlapping samples (dataset above). WGS from PCAWG, SNP array, and WES from GDC portal.

 

6. cellline-batch1.zip & cellline-batch1.zip

 

GCAP results of cell line batch 1 and batch 2.

 

7. AA_cellline_wgs.zip

AA software results for cell line batch 1.

 

8. Batch2_AA_summary.xlsx

AA software results for cell line batch 2.

 

9. FISH-for-supp-file.zip

Extended raw FISH images from 12 CRC samples.

 

10. SNU216.zip

Extended AA and GCAP analysis on SNU216.

 

11. aa_ffpe.zip and AA_summary_table_of_6_erbb2_ffpe_samples.xlsx

Extended AA running files (all results) and result summary data for 6 GCAP predicted ERBB2 amp clinical samples.

 

12. source data of fig.4

 

13. source data of supp fig.2 subplots

 

13. source data of supp fig.15

 

14. GCAP result data objects for three ICB cohorts. Both gene-level and sample-level data included.

 

15. PDX-P68: processed (AA and CNV) data of P68 from WGS and WES data.

 

16. source data of supp fig.13

 

17. updated supplementary figure 14
DOI: 10.5281/zenodo.7272630
title: ecDNA machine learning modeling
title: The source data of supplementary figure 13 in the accompanying article table has been found to have issues, which were identified as a result of improper Excel operation. Here, we have uploaded the correct data table

description: 1. Today (2024-06-27), we discovered an issue with the labeling of sample groups in one of the supplementary figures (Supplementary Figure 14c) in our published article. We have corrected the figure and present it here, and we extend our apologies to all readers for any confusion this may have caused (although no report received).

2. The source data of supplementary figure 13 in the accompanying article table has been found to have issues, which were identified as a result of improper Excel operation. Here, we have uploaded the correct data table

--------------------------------------------------

 

1. ecDNA_cargo_gene_modeling_data.csv.gz

The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes.

library(data.table)

data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds")

colnames(data)[3] = "total_cn"

data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",")

 

2. gcap_pcawg_WGS_result.tar.gz

GCAP analysis results for PCAWG allele-specific copy number profiles derived from WGS.

 

3. gcap_tcga_snp6_result.tar.gz

GCAP analysis results for TCGA allele-specific copy number profiles derived from SNP6 array.

 

4. gcap_Changkang_WES_result.tar.gz

GCAP analysis results for SYSUCC Changkang allele-specific copy number profiles derived from tumor-normal paired WES.

 

5. tcga_overlap_gene_wgs.rds, tcga_overlap_gene_snp.rds and tcga_overlap_gene_wes.rds

These datasets contain TCGA gene-level copy number results in R data format from overlapping samples (dataset above). WGS from PCAWG, SNP array, and WES from GDC portal.

 

6. cellline-batch1.zip & cellline-batch1.zip

 

GCAP results of cell line batch 1 and batch 2.

 

7. AA_cellline_wgs.zip

AA software results for cell line batch 1.

 

8. Batch2_AA_summary.xlsx

AA software results for cell line batch 2.

 

9. FISH-for-supp-file.zip

Extended raw FISH images from 12 CRC samples.

 

10. SNU216.zip

Extended AA and GCAP analysis on SNU216.

 

11. aa_ffpe.zip and AA_summary_table_of_6_erbb2_ffpe_samples.xlsx

Extended AA running files (all results) and result summary data for 6 GCAP predicted ERBB2 amp clinical samples.

 

12. source data of fig.4

 

13. source data of supp fig.2 subplots

 

13. source data of supp fig.15

 

14. GCAP result data objects for three ICB cohorts. Both gene-level and sample-level data included.

 

15. PDX-P68: processed (AA and CNV) data of P68 from WGS and WES data.

 

16. source data of supp fig.13

 

17. updated supplementary figure 14
DOI: 10.5281/zenodo.7272631
title: ecDNA cargo gene modeling

description: The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes. <pre><code>library(data.table) data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds") colnames(data)[3] = "total_cn" data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",") </code></pre>
DOI: 10.5281/zenodo.7375441
title: ecDNA cargo gene modeling

description: 1. ecDNA_cargo_gene_modeling_data.csv.gz The dataset contains features from 386 TCGA tumors for modeling ecDNA cargo gene prediction. It was converted from R data format with the following code. NOTE: columns 'sample' and 'gene_id' are not used for actual modeling but for identifying, and sampling purposes. <pre><code>library(data.table) data = readRDS("~/../Downloads/ecDNA_cargo_gene_modeling_data.rds") colnames(data)[3] = "total_cn" data.table::fwrite(data, file = "~/../Downloads/ecDNA_cargo_gene_modeling_data.csv.gz", sep = ",") </code></pre> 2. gcap_pcawg_WGS_result.tar.gz GCAP analysis results for PCAWG allele-specific copy number profiles derived from WGS. 3. gcap_tcga_snp6_result.tar.gz GCAP analysis results for TCGA allele-specific copy number profiles derived from SNP6 array. 4. gcap_Changkang_WES_result.tar.gz GCAP analysis results for SYSUCC Changkang allele-specific copy number profiles derived from tumor-normal paired WES. 5. tcga_overlap_gene_wgs.rds, tcga_overlap_gene_snp.rds and tcga_overlap_gene_wes.rds These datasets contain TCGA gene-level copy number results in R data format from overlapping samples (dataset above). WGS from PCAWG, SNP array, and WES from GDC portal. 6. cell_line_gcap.tsv and cellline_amp_overlap.RData GCAP analysis results for cancer cell line copy number profiles and overlapping analysis results. Other analysis results please refer to our manuscript. 7. AA_cellline_wgs.zip AA software results for cell line WGS.