Dataset

SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS

Tumour-normal data used in Additional file 2 Table S3.

Evaluation results

32 evaluations · 1,536 results. Different protocols are not a single leaderboard.

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Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	55.4% F1 (INDELs, average over the 47 purity-coverage pairs as printed) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'Average', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	44.9% F1 (INDELs, tumour SPP_100x_10%T with normal SPP_100x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_100x_10%T vs SPP_100x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	83.4% F1 (INDELs, tumour SPP_100x_100%T with normal SPP_100x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_100x_100%T vs SPP_100x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	70.9% F1 (INDELs, tumour SPP_100x_20%T with normal SPP_100x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_100x_20%T vs SPP_100x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	20.1% F1 (INDELs, tumour SPP_100x_5%T with normal SPP_100x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_100x_5%T vs SPP_100x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	82.5% F1 (INDELs, tumour SPP_100x_50%T with normal SPP_100x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_100x_50%T vs SPP_100x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	83.3% F1 (INDELs, tumour SPP_100x_75%T with normal SPP_100x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_100x_75%T vs SPP_100x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	0.3% F1 (INDELs, tumour SPP_10x_10%T with normal SPP_10x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_10x_10%T vs SPP_10x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	42.5% F1 (INDELs, tumour SPP_10x_100%T with normal SPP_10x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_10x_100%T vs SPP_10x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	3.7% F1 (INDELs, tumour SPP_10x_20%T with normal SPP_10x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_10x_20%T vs SPP_10x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	0% F1 (INDELs, tumour SPP_10x_5%T with normal SPP_10x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_10x_5%T vs SPP_10x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	22.1% F1 (INDELs, tumour SPP_10x_50%T with normal SPP_10x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_10x_50%T vs SPP_10x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	35.6% F1 (INDELs, tumour SPP_10x_75%T with normal SPP_10x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_10x_75%T vs SPP_10x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	69.9% F1 (INDELs, tumour SPP_200x_10%T with normal SPP_200x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_200x_10%T vs SPP_200x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	83.9% F1 (INDELs, tumour SPP_200x_100%T with normal SPP_200x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_200x_100%T vs SPP_200x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	80.6% F1 (INDELs, tumour SPP_200x_20%T with normal SPP_200x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_200x_20%T vs SPP_200x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	44.6% F1 (INDELs, tumour SPP_200x_5%T with normal SPP_200x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_200x_5%T vs SPP_200x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	84.2% F1 (INDELs, tumour SPP_200x_50%T with normal SPP_200x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_200x_50%T vs SPP_200x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	84.3% F1 (INDELs, tumour SPP_200x_75%T with normal SPP_200x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_200x_75%T vs SPP_200x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	72.9% F1 (INDELs, tumour SPP_300x_10%T with normal SPP_300x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_300x_10%T vs SPP_300x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	84.2% F1 (INDELs, tumour SPP_300x_100%T with normal SPP_300x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_300x_100%T vs SPP_300x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	80.4% F1 (INDELs, tumour SPP_300x_20%T with normal SPP_300x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_300x_20%T vs SPP_300x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	50.6% F1 (INDELs, tumour SPP_300x_5%T with normal SPP_300x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_300x_5%T vs SPP_300x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	83.7% F1 (INDELs, tumour SPP_300x_50%T with normal SPP_300x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_300x_50%T vs SPP_300x_100%N', column 'DRAGEN'
Configuration: DRAGEN v3.7.5 (Sahraeian et al. 2022)	Protocol: SEQC2 HCC1395 tumour purity, coverage and normal contamination, indel F1 (Sahraeian et al. 2022 Table S3) Dataset: SEQC2 tumour-normal titration: HCC1395 gDNA mixed with HCC1395BL gDNA at 5-100% tumour purity, 10x-300x WGS	83.4% F1 (INDELs, tumour SPP_300x_75%T with normal SPP_300x_100%N) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DRAGEN on SEQC2 tumour-normal titration, INDELs (Sahraeian et al. 2022) somatic-neusomatic-20261010-protocol-sahraeian2022-titration-indel Aggregation: Not reported Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample; Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Additional file 2 Table S3, INDELs section, row 'SPP_300x_75%T vs SPP_300x_100%N', column 'DRAGEN'

Source checking is not independent reproduction. Release 2026-10-10-457d7eaef7d6.

Research readiness

0 of 4 readiness checks met. These checks assess whether the evidence supports a reproducible investigation; a source-checked score alone does not meet them.

Readiness checks, gaps and artifacts

Release 2026-10-10-457d7eaef7d6 · Evidence verified: Not verified

Evidence incomplete

Replay metrics

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File checksums match the recorded files: not yet verified
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Verified: Not verified

Evidence incomplete

Investigate discrepancies

Replay evidence includes annotations and an assessment of dependence. Unknown independence permits descriptive analysis only.

Missing or unresolved evidence

No verified artifact manifest is linked to this exact record.
File checksums match the recorded files: not yet verified
Predictions are matched to the right samples: not yet verified
Score meaning and direction are confirmed: not yet verified
Metrics are recomputed from the saved predictions: not yet verified
Sample annotations are recorded: not yet verified
Dependence between samples is assessed: not yet verified

Verified: Not verified

Evidence incomplete

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Missing or unresolved evidence

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File checksums match the recorded files: not yet verified
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Score meaning and direction are confirmed: not yet verified
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Verified: Not verified

Evidence incomplete

Validate independently

Separate data and exposure records support an independent test.

Missing or unresolved evidence

No verified artifact manifest is linked to this exact record.
File checksums match the recorded files: not yet verified
Predictions are matched to the right samples: not yet verified
Score meaning and direction are confirmed: not yet verified
Independent validation data exist: not yet verified
Overlap with training data is checked: not yet verified

Verified: Not verified

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Dataset and evaluation context

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Evidence

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Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

14 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-10-457d7eaef7d6
Property and statement	Original source and location	Review and provenance
Accession NCBI SRA SRP162370 Context-only references	Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample Original source ↗ Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML Retrieved: 2026-10-10T06:04:11Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.accession` Source artifact SHA-256: `78dbe540c2558585bc7537e0e6563706fdaa329b2708e5dc82b77074379b4a6e` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Accession NCBI SRA SRP162370 Context-only references	Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) Original source ↗ Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 13059_2021_2592_MOESM2_ESM.pdf Retrieved: 2026-10-10T06:04:16Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.accession` Source artifact SHA-256: `10a109d80f6f49446ea84bd9f7f6b31c20d634516c8666376ac8a8f51f3236d0` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Assay Paired tumour-normal whole-genome sequencing, Trimmomatic, BWA-MEM 0.7.15, Picard MarkDuplicates Context-only references	Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample Original source ↗ Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML Retrieved: 2026-10-10T06:04:11Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.assay` Source artifact SHA-256: `78dbe540c2558585bc7537e0e6563706fdaa329b2708e5dc82b77074379b4a6e` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Assay Paired tumour-normal whole-genome sequencing, Trimmomatic, BWA-MEM 0.7.15, Picard MarkDuplicates Context-only references	Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) Original source ↗ Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 13059_2021_2592_MOESM2_ESM.pdf Retrieved: 2026-10-10T06:04:16Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.assay` Source artifact SHA-256: `10a109d80f6f49446ea84bd9f7f6b31c20d634516c8666376ac8a8f51f3236d0` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Population 42 purity-coverage pairs (5, 10, 20, 50, 75 and 100% tumour at 10x, 30x, 50x, 80x, 100x, 200x and 300x, pure normal) and 5 pairs at 80x with a 95% pure normal (10-100% tumour) Context-only references	Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample Original source ↗ Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML Retrieved: 2026-10-10T06:04:11Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.population` Source artifact SHA-256: `78dbe540c2558585bc7537e0e6563706fdaa329b2708e5dc82b77074379b4a6e` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Population 42 purity-coverage pairs (5, 10, 20, 50, 75 and 100% tumour at 10x, 30x, 50x, 80x, 100x, 200x and 300x, pure normal) and 5 pairs at 80x with a 95% pure normal (10-100% tumour) Context-only references	Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) Original source ↗ Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 13059_2021_2592_MOESM2_ESM.pdf Retrieved: 2026-10-10T06:04:16Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.population` Source artifact SHA-256: `10a109d80f6f49446ea84bd9f7f6b31c20d634516c8666376ac8a8f51f3236d0` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Source location Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Context-only references	Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample Original source ↗ Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML Retrieved: 2026-10-10T06:04:11Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.source_locator` Source artifact SHA-256: `78dbe540c2558585bc7537e0e6563706fdaa329b2708e5dc82b77074379b4a6e` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Source location Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Context-only references	Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) Original source ↗ Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 13059_2021_2592_MOESM2_ESM.pdf Retrieved: 2026-10-10T06:04:16Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.source_locator` Source artifact SHA-256: `10a109d80f6f49446ea84bd9f7f6b31c20d634516c8666376ac8a8f51f3236d0` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Split Evaluation region: the 50% of the SEQC2 high-confidence genome held out from SEQC-WGS-GT-50 training Context-only references	Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample Original source ↗ Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML Retrieved: 2026-10-10T06:04:11Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.split` Source artifact SHA-256: `78dbe540c2558585bc7537e0e6563706fdaa329b2708e5dc82b77074379b4a6e` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Split Evaluation region: the 50% of the SEQC2 high-confidence genome held out from SEQC-WGS-GT-50 training Context-only references	Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) Original source ↗ Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process' Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 13059_2021_2592_MOESM2_ESM.pdf Retrieved: 2026-10-10T06:04:16Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.split` Source artifact SHA-256: `10a109d80f6f49446ea84bd9f7f6b31c20d634516c8666376ac8a8f51f3236d0` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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Sources and history

Release 2026-10-10-457d7eaef7d6 · Record review: source checked

2 source records and release history

Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample · Original source · Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML
Sahraeian et al. 2022, Additional file 2: Supplementary Tables S1-S10 (13059_2021_2592_MOESM2_ESM.pdf) · Original source · 13059_2021_2592_MOESM2_ESM.pdf

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Technical metadata and extraction receipts

Stable ID: somatic-neusomatic-20261010-data-sahraeian2022-titration

areas: dna-genomes
contexts: clinical_research
population: 42 purity-coverage pairs (5, 10, 20, 50, 75 and 100% tumour at 10x, 30x, 50x, 80x, 100x, 200x and 300x, pure normal) and 5 pairs at 80x with a 95% pure normal (10-100% tumour)
split: Evaluation region: the 50% of the SEQC2 high-confidence genome held out from SEQC-WGS-GT-50 training
assay: Paired tumour-normal whole-genome sequencing, Trimmomatic, BWA-MEM 0.7.15, Picard MarkDuplicates
accession: NCBI SRA SRP162370
source locator: Additional file 2 Table S3 row labels; Results; Methods 'SEQC2 tumor-normal sequencing data and ground truth' and 'Evaluation process'
missing metadata: version: reason: unreported; note: Truth set is SEQC2 v1.0; data release not otherwise stated

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