Somatic input in O'Connell et al. 2023.
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Release 2026-10-09-ba02f2f4a36e · Evidence verified: Not verified
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44 evaluations · 168 results. Different protocols are not a single leaderboard.
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: LoFreq execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 4.1 compute-cost us-dollar · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceLoFreq on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-lofreq Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 23 (AWS, C6i.8xlarge, LoFreq), column 'Cost ($)' |
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: LoFreq execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 180 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceLoFreq on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-lofreq Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 23 (AWS, C6i.8xlarge, LoFreq), column 'Time (min)' |
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: LoFreq execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 3 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceLoFreq on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-lofreq Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 23 (AWS, C6i.8xlarge, LoFreq), column 'Time (h)' |
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: Muse execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 9.6 compute-cost us-dollar · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMuse on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-muse Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 34 (AWS, C6i.8xlarge, Muse), column 'Cost ($)' |
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: Muse execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 425 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMuse on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-muse Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 34 (AWS, C6i.8xlarge, Muse), column 'Time (min)' |
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: Muse execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 7.09 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMuse on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-muse Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 34 (AWS, C6i.8xlarge, Muse), column 'Time (h)' |
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: Mutect2 execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 9.4 compute-cost us-dollar · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMutect2 on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-mutect2 Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 45 (AWS, C6i.8xlarge, Mutect2), column 'Cost ($)' |
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: Mutect2 execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 415 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMutect2 on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-mutect2 Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 45 (AWS, C6i.8xlarge, Mutect2), column 'Time (min)' |
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: Mutect2 execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 6.91 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMutect2 on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-mutect2 Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 45 (AWS, C6i.8xlarge, Mutect2), column 'Time (h)' |
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: SomaticSniper execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 8.88 compute-cost us-dollar · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceSomaticSniper on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-somaticsniper Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 56 (AWS, C6i.8xlarge, SomaticSniper), column 'Cost ($)' |
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: SomaticSniper execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 392 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceSomaticSniper on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-somaticsniper Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 56 (AWS, C6i.8xlarge, SomaticSniper), column 'Time (min)' |
| Configuration: CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) | Protocol: SomaticSniper execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 6.53 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceSomaticSniper on CPU tools on AWS c6i.8xlarge (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-somaticsniper Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 56 (AWS, C6i.8xlarge, SomaticSniper), column 'Time (h)' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: LoFreq execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 29.6 compute-cost us-dollar · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceLoFreq on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-lofreq Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 24 (AWS, GPU2, LoFreq), column 'Cost ($)' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: LoFreq execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | − 625.07% cost-saving percent · higher Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceLoFreq on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-lofreq Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 24 (AWS, GPU2, LoFreq), column '% cost-savings' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: LoFreq execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 145 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceLoFreq on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-lofreq Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 24 (AWS, GPU2, LoFreq), column 'Time (min)' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: LoFreq execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 2.42 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceLoFreq on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-lofreq Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 24 (AWS, GPU2, LoFreq), column 'Time (h)' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: LoFreq execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 1.24 speedup unitless · higher Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceLoFreq on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-lofreq Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 24 (AWS, GPU2, LoFreq), column 'Fold acceleration' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: Muse execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 13.3 compute-cost us-dollar · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMuse on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-muse Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 35 (AWS, GPU2, Muse), column 'Cost ($)' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: Muse execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | − 37.97% cost-saving percent · higher Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMuse on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-muse Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 35 (AWS, GPU2, Muse), column '% cost-savings' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: Muse execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 65.2 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMuse on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-muse Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 35 (AWS, GPU2, Muse), column 'Time (min)' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: Muse execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 1.09 runtime hour · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMuse on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-muse Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 35 (AWS, GPU2, Muse), column 'Time (h)' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: Muse execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 6.52 speedup unitless · higher Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMuse on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-muse Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 35 (AWS, GPU2, Muse), column 'Fold acceleration' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: Mutect2 execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 5.79 compute-cost us-dollar · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMutect2 on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-mutect2 Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 46 (AWS, GPU2, Mutect2), column 'Cost ($)' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: Mutect2 execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 38.3% cost-saving percent · higher Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMutect2 on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-mutect2 Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 46 (AWS, GPU2, Mutect2), column '% cost-savings' |
| Configuration: Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) | Protocol: Mutect2 execution on CPU and GPU cloud and DGX machines (O'Connell et al. 2023 Table 1) Dataset: Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 | 28.4 runtime minute · lower Uncertainty: Not reported by the source: Single recorded run per cell; no repeats or intervals printed Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMutect2 on Parabricks 3.7.0-1, 2 GPUs on AWS (O'Connell et al. 2023) model-execution-20261009-protocol-oconnell2023-mutect2 Aggregation: Not reported Accelerating genomic workflows using NVIDIA Parabricks · Table 1, row 46 (AWS, GPU2, Mutect2), column 'Time (min)' |
Source checking is not independent reproduction. Release 2026-10-09-ba02f2f4a36e.
A dataset supplies biological observations. The evaluation protocol defines how those observations are split, used and scored.
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
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.
5 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.population HG002 30x BAM after MarkDuplicates and BQSR, with 198 SNVs at random VAF 0.001-0.4 from ICGC donor DO32536 sites Context-only references | Accelerating genomic workflows using NVIDIA Parabricks Methods 'Sampling and algorithms' paragraph 3 Version: BMC Bioinformatics 24:221, published 2023-05-31; PMC10230726 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| attributes.source_locator Methods 'Sampling and algorithms' paragraph 3 Context-only references | Accelerating genomic workflows using NVIDIA Parabricks Methods 'Sampling and algorithms' paragraph 3 Version: BMC Bioinformatics 24:221, published 2023-05-31; PMC10230726 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| attributes.split Single synthetic tumour, one recorded run per configuration Context-only references | Accelerating genomic workflows using NVIDIA Parabricks Methods 'Sampling and algorithms' paragraph 3 Version: BMC Bioinformatics 24:221, published 2023-05-31; PMC10230726 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| description Somatic input in O'Connell et al. 2023. Context-only references | Accelerating genomic workflows using NVIDIA Parabricks Methods 'Sampling and algorithms' paragraph 3 Version: BMC Bioinformatics 24:221, published 2023-05-31; PMC10230726 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| name Synthetic tumour BAM: HG002 30x with 198 SNVs added by SomatoSim v1.0.0 Context-only references | Accelerating genomic workflows using NVIDIA Parabricks Methods 'Sampling and algorithms' paragraph 3 Version: BMC Bioinformatics 24:221, published 2023-05-31; PMC10230726 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Release 2026-10-09-ba02f2f4a36e · Record review: source checked
Stable ID: model-execution-20261009-data-oconnell2023-hg002-somatosim