It is challenging to identify somatic variants from high-throughput sequence reads due to
tumor heterogeneity, sub-clonality, and sequencing artifacts. In this study, we evaluated the …

Background Next-generation sequencing (NGS) allows unbiased, in-depth interrogation of
cancer genomes. Many somatic variant callers have been developed yet accurate …

Motivation: Somatic variant calling typically requires paired tumor-normal tissue samples.
Yet, paired normal tissues are not always available in clinical settings or for archival …

Detection of somatic mutations holds great potential in cancer treatment and has been a
very active research field in the past few years, especially since the breakthrough of the next …

Cancer genomic analysis requires accurate identification of somatic variants in sequencing
data. Manual review to refine somatic variant calls is required as a final step after automated …

Background Various approaches to calling single-nucleotide variants (SNVs) or insertion-or-
deletion (indel) mutations have been developed based on next-generation sequencing …

Identification of somatic mutations in tumor samples is commonly based on statistical
methods in combination with heuristic filters. Here we develop VarNet, an end-to-end deep …

Detection of somatic mutations in tumor samples is important in the clinic, where treatment
decisions are increasingly based upon molecular diagnostics. However, accurate detection …

Publications comparing variant caller algorithms present discordant results with
contradictory rankings. Caller performances are inconsistent and wide ranging, and …

Somatic structural variants (SVs), which are variants that typically impact> 50 nucleotides,
play a significant role in cancer development and evolution but are notoriously more difficult …