Analyzing Transcript-level Properties of Mutation Data in VCF Files
The tool will allow users to analyze mutation data from variant call format (VCF) files. The purpose of this tool is to streamline the analysis of transcription-related effects of mutations, such as analyzing whether the mutations are synonymous or nonsynonymous at the amino acid level, whether they have any deleterious effects and so on. The tool also enables the visualization of mutations in exonic regions, allowing the exploration of how these transcription-related effects vary along the length of a gene. It has the functionality to map the genomic location of mutations to their location on the coding sequence (CDS) of the transcript, with the introns removed.
This R package extends existing functionality for the analysis of mutations stored in VCF files. Although many tools exist for the analysis of mutations, there are none to the best of my knowledge that provides a streamlined workflow for the visual exploration of coding sequence mutations and their effects on the protein product. This tool aims to fill that gap in existing software, as well as also provide functionality to map these mutation properties along the length of a gene to see where specific kinds of mutations localize on the gene. This information can be relevant for, for example, uncovering biological effects such as mutation bias on particular ends of genes or technical effects such as bias towards the 3’ or 5’ ends of genes in particular RNA sequencing platforms. Therefore, we hope that this package will enable exploratory analysis of such effects and thus guide further downstream analysis of mutation data.
This package was built using R version 4.4.2 on an aarch64-apple-darwin20 platform, running under macOS Ventura 13.2.1.
You can install the development version of MutTranscript like so:
install.packages("devtools")
library("devtools")
devtools::install_github("jahink17/MutTranscript", build_vignettes = TRUE)
library("MutTranscript")To run the Shiny app:
runBinnedPlotSingleGene()ls("package:<PackageName>")
data(package = "<PackageName>") # optional
browseVignettes("<PackageName>")The package contains 5 functions: 1. loadVcf() 2. annotateVcf() 3. binnedByDistancePlotV2() 4. binnedByDistancePlotSingleGene() 5. runBinnedPlotSingleGene()
The functions were contributed by Jahin Kabir, with help from the packages cited below. LoadVcf() loads a VCF file from a given file path and makes sure the chromosome names are in the appropriate format for downstream analysis. annotateVcf() annotates the VCF file to identify coding mutations and returns their annotated information, such as amino acid change. binnedByDistancePlotV2() plots the distribution of mutation types along the normalized length of genes across all genes in the genome, and was written by Jahin Kabir with some assistance from GenAI for help with ggplot() functions. binnedByDistancePlotSingleGene() does the same thing for a single gene, and was modified from binnedByDistancePlotV2() by Jahin.
Minimal help was used from GenAI, with the binnedByDistancePlot()
function, to get help with binning the mutations by distance. AI was
also used to assist with building the Shiny app, and the code output
from GenAI was modified by Jahin Kabir.
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This package was developed as part of an assessment for 2024 BCB410H:
Applied Bioinformatics course at the University of Toronto, Toronto,
CANADA. MutTranscript welcomes issues, enhancement requests, and other
contributions. To submit an issue, use the GitHub issues.