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A somatic reference standard for cancer genome sequencing with COLO829

Identification of somatic alterations in cancer has become feasible with the massive adoption of next generation sequencing. However, due to variability in sequencing and informatics pipelines, a common somatic reference is needed. We thus performed paired whole genome sequencing of a metastatic melanoma cell line (COLO829) and a matched lymphoblastoid line (COLO829BL) across three institutions (TGen, Illumina, Genome Sciences Centre at the British Columbia Cancer Agency). We performed a meta-analysis of all data, in combination with the originally reported analysis of these cell lines by Pleasance et al (PMID: 20016485), and report a somatic reference standard based on consensus events. DNA extractions, library preparation, sequencing, and analysis were separately performed at each site. Results were compiled with sequence data previously generated for the cell lines to identify true positive variants, collectively representing a somatic reference standard. Overall, common somatic events include point mutations, small insertion/deletions, and genes affected by concurrent copy number changes. We additionally show divergence of somatic mutations in COLO829 associated with differences in cell line lineage. We present this reference to the community as a standard for enabling interpretation and identification of somatic mutations across institutions and analytical pipelines.

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Dataset ID Description Technology Samples
EGAD00001002142 24
EGAD00001007920 PromethION 1
Publications Citations
A somatic reference standard for cancer genome sequencing.
Sci Rep 6: 2016 24607
28
Deep whole-genome sequencing of 3 cancer cell lines on 2 sequencing platforms.
Sci Rep 9: 2019 19123
18
Varlociraptor: enhancing sensitivity and controlling false discovery rate in somatic indel discovery.
Genome Biol 21: 2020 98
11
Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase.
Genome Biol 22: 2021 68
22
Accurate somatic variant detection using weakly supervised deep learning.
Nat Commun 13: 2022 4248
5
TMBur: a distributable tumor mutation burden approach for whole genome sequencing.
BMC Med Genomics 15: 2022 190
1
Simple combination of multiple somatic variant callers to increase accuracy.
Sci Rep 13: 2023 8463
1