ClairS and ClairS-TO
These are complementary tools, as ClairS is designed for long-read somatic small variant calling (implying availability of matched normal tissue data), while ClairS-TO specifically addresses the tumor-only scenario for somatic variant calling.
About ClairS
HKU-BAL/ClairS
ClairS - a deep-learning method for long-read somatic small variant calling
This tool helps cancer researchers and clinical geneticists identify subtle genetic changes (somatic small variants) that occur in a tumor but not in healthy tissue. It takes raw DNA sequencing data from paired tumor and normal samples (specifically long-read data from Oxford Nanopore or PacBio, and also Illumina data) and outputs a list of these somatic variants, indicating what changed and where. This allows scientists to pinpoint mutations relevant to cancer development or treatment.
About ClairS-TO
HKU-BAL/ClairS-TO
ClairS-TO - a deep-learning method for tumor-only somatic variant calling
This project helps cancer researchers and clinicians identify somatic small variants in tumor samples using long-read sequencing data. It takes raw sequencing reads from a tumor sample as input and outputs a list of potential somatic variants, even without a matched normal sample. This tool is designed for specialists in cancer genomics or molecular pathology who need to precisely detect mutations specific to a tumor.
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