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Integrative quality control of cancer somatic mutations with Cancer Mutation Quality Control

The quality control of cancer somatic mutations has a great significance in the research of cancer genomics. It helps reduce the noise, systematic bias, as well as the false positive rate in dataset, and to pick out candidate mutations related to tumorigenesis. However, existing tools were not designed especially for cancer somatic mutations, and parameters and filtering standards used are different among them. Besides, there is no such a platform, database or tool stores or summarizes the standards for filtration of cancer somatic mutations applied in previous studies, which increases the time and energy spent on related research.

Therefore, we present this R package, CaMutQC, for the comprehensive filtration and selection of cancer somatic mutations. CaMutQC is able to filter false positive mutations generated due to technical issues, as well as to select candidate cancer mutations through a series of well-structured functions by labeling mutations with various flags.

Also, a detailed and vivid filter report will be offered after completing a whole filtration or selection section.

Installation

#  install the latest version from GitHub
if(!require(devtools)) install.packages("devtools")
devtools::install_github("likelet/CaMutQC")

Usage

This is a simple workflow of CaMutQC.

CaMutQC framework

A detailed manual can be found here.

Author

This software was mainly developed by:

Supervised by

  • Jian Ren from School of Life Sciences in Sun Yat-sen University
  • Qi Zhao from Bioinformatic Center of Sun Yat-sen University Cancer Center

Maintainer

Xin Wang

Citation (AACR 2022 abstract)

Xin Wang, Jian Ren, Qi Zhao. Integrative quality control of cancer somatic mutations with CaMutQC [abstract]. In: Proceedings of the 113th Annual Meeting of the American Association for Cancer Research; 2022 April 8-13; New Orleans LA. Philadelphia (PA): AACR; 2022. Abstract nr 5004

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