Rigorous software pipeline for clinical somatic mutation analyses of solid tumors
Stoimenov, I.; Rashyna, M.; Adlerteg, T.; Nunes, L.; Ekstrom, J.; Ljungstrom, V.; Mathot, L.; Cheong, I.; Sjoblom, T.
Show abstract
Mutational analyses of tumor DNA guide the use of targeted therapies and checkpoint inhibitors in management of solid tumors. Reducing false positive mutation calls without compromising sensitivity as gene panels increase in size, and whole exome and genome sequencing enters clinical use, remains a major challenge. Aiming for robust somatic mutation analyses in the clinical setting, we have developed VARify, an integrated, accurate and computationally efficient software for cancer genome analyses encompassing all steps from pre-processing of sequencing reads to mutation identification. Benchmarking to two state-of-the-art open-source somatic mutation analysis pipelines demonstrated accurate detection of clinically actionable point mutations, all while strongly reducing the number of false positive mutations reported, at comparable or faster speed. Further, the VARify output classified microsatellite unstable colorectal cancers by tumor mutation burden better than the other pipelines. In comparisons where the same tumors were subjected to different panel enrichment and sequencing technologies, VARify had the most consistent intersection of consensus mutations. False positive calls were produced when the same data was used as tumor and reference by the other pipelines, while VARify did not produce such calls. The calling uniformity across sequencing technologies of VARify and its tumor-only analysis derivative pipeline ALTOmate was also demonstrated. Taken together, these two novel pipelines can improve clinical mutation analysis to the benefit of cancer patients.
Matching journals
The top 11 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Tumor break load quantitates structural variant-associated genomic instability with biological and clinical relevance across cancers 93%
- A single-cell based precision medicine approach using glioblastoma patient-specific models 93%
- Image-Based Consensus Molecular Subtyping in Rectal Cancer Biopsies and Response to Neoadjuvant Chemoradiotherapy 92%
Similar papers in this journal
- The Gastric Cancer Registry: A Genomic Translational Resource for Multidisciplinary Research in Stomach Malignancies 92%
- Molecular subtypes of high grade serous ovarian cancer across racial groups and gene expression platforms 92%
- Genetic analysis of functional rare germline variants across 9 cancer types from the DiscovEHR study 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.