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ShainLab/Single_Cell_Somatic_Mutation_Caller: Single Cell Somatic Mutation Caller

Authors: Tandukar, Bishal; Deivendran, Delahny; Sharma, Harsh; Chang, Darwin; Shain, Alan;

ShainLab/Single_Cell_Somatic_Mutation_Caller: Single Cell Somatic Mutation Caller

Abstract

This release provides the first public version of the Single Cell Somatic Mutation Caller developed in the Shain Lab. The software implements a workflow for identifying somatic mutations from sequencing data derived from clonally expanded single-cell samples. The pipeline includes scripts for processing alignment files, identifying candidate somatic variants, and generating mutation calls suitable for downstream evolutionary and clonal analyses. It is designed to support studies investigating somatic mutation accumulation and clonal dynamics in normal tissues and cancer. This repository was used as part of the computational framework for somatic mutation analyses described in related studies of epidermis and squamous cell carcinoma evolution. License: MIT License Please cite the Zenodo DOI associated with this release when using this software in publications. Changes in v1.0.0 Initial public release of the Single Cell Somatic Mutation Caller Scripts for somatic mutation detection from sequencing alignments Documentation and usage instructions included in the repository Full Changelog: https://github.com/ShainLab/Single_Cell_Somatic_Mutation_Caller/commits/v1.0.0

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Related to Research communities
Cancer Research