A User-Friendly R Package for Nanopore Sequencing Mutation Analysis. Offering A Efficient, Accessible Workflow from FASTQ File Alignment to Visualizations.

LegitXMut is an R package designed for the analysis of genetic variants, specifically designed for workflows that handle Nanopore sequencing data. The workflow of the package involves aligning sequencing reads, updating chromosome names in VCF files, and visualizing mutation data, which enhance the efficiency and accessibility of mutation analysis in bioinformatics pipelines. LegitXMut integrates with widely used bioinformatics tools like Rsubread, VariantAnnotation, GenomicAlignments, and others, to help users to perform end-to-end genomic variant analysis within ONE PACKAGE and THREE FUNCTIONS. Users have to change the file paths to local paths for tests and usage.

This package fills a gap in bioinformatics workflows by allowing direct handling of FASTQ, and VCF files for visualization of mutations, which can aid in exploratory data analysis and the interpretation of mutation patterns across various chromosomes. Unlike many existing tools, LegitXMut is uniquely focused on a complete solution from alignment to visualization in R language, offering functions for generating compelling graphical outputs such as heatmaps, rainfall plots, and manhattan plots to illustrate mutation distributions and result confidences. The LegitXMut package was developed using R version 4.4.1 (June, 2024), Platform: x86_64-w64-mingw32/x64 (64-bit), running under Windows 11.

# Install devtools if needed
install.packages("devtools")
library(devtools)

# Install LegitXMut from GitHub with vignettes
devtools::install_github("ZhenghaoXiao/LegitXMut", build_vignettes = TRUE)
library(LegitXMut)

# Rtools is a mandatory requirement for this package
# If errors occur mentioning any dependencies was failed to install
# Please manually install them on Bioconductor (Likely to be VariantAnnotation and GenomicAlignments)
# For Example:
#if (!require("BiocManager", quietly = TRUE))
    #install.packages("BiocManager")
#BiocManager::install("VariantAnnotation")

#if (!require("BiocManager", quietly = TRUE))
    #install.packages("BiocManager")

#BiocManager::install("GenomicAlignments")

To run the Shiny app:

LegitXMut::runLegitXMut()

The overview of the package:

ls("package:LegitXMut")
data(package = "LegitXMut") # empty
# Demo data of this package was downloaded from NCBI, as listed in the reference
# Users can access them in inst/exdata/, as mentioned in the function examples and vignettes
browseVignettes("LegitXMut")

LegitXMut provides the following functions for now: - alignment_FASTQ:This function creates BAMand VCF file by aligning a FASTQ file to a provided reference genome in FASTA format and calls variant. It allows the setting of maximal insertions and deletions(indel) mutations and mismatches criteria for quality control and optimization. The result .VCF file should be input into update_vcf and plot_vcf_mutation_data later on.

-update_vcf:This tool updates the chromosome names in a VCF file by extracting chromosomal mappings from a reference genome in FASTA format. It ensures the workflows that demand multiple chromosomes and whole genome analysis by producing a modified VCF file with standardized chromosome names.

-plot_vcf_mutation_data:This function takes the VCF file generated from update_vcf or users can input external files and use them to create different mutation visualizations. The three graphic types that users can select from—“heatmap,” “manhattan,” and “rainfall”—each offers distinct viewpoints on mutation data, including mutation density, confidences of the result, and inter-variant distances across chromosomes.

The author of LegitXMut is Zhenghao Xiao. The package provides three functions to analyze genetic variation by allowing users to align sequence reads to reference genome, standardize chromosome names, and visualize mutation patterns in one package.

alignment_FASTQ(): Rsubread and GenomicAlignments was employed to align a FASTQ file to a reference genome, generating BAM and VCF files while allowing quality control through configurable parameters for indels and mismatches. OpenAI was used for debugging suggestions and potential function suggestions only, and the function was fully constructed and written by the author.

update_vcf(): This function utilizes VariantAnnotation, stringr and GenomeInfoDb to update chromosome names in VCF files according to a reference genome FASTA file, the updated file will used for visualizations. OpenAI was used for debugging suggestions and potential function suggestions only, and the function was fully constructed and written by the author.

plot_vcf_mutation_data(): This function requires VariantAnnotation, GenomicRanges, ggplot2, ComplexHeatmap, SummarizedExperiment, dplyr, stats, and circlize. Using a variety of plot patterns (“heatmap,” “manhattan,” and “rainfall”), this tool visualizes mutation data from VCF files to help with understanding chromosome-to-chromosome inter-variant distances, mutation frequency density, and distribution.OpenAI was used for debugging suggestions and potential function suggestions only, and the function was fully constructed and written by the author.

1.BioRender. (2024). Image created by Zhenghao Xiao. Retrieved November 5, 2024, from https://app.biorender.com/

2.Chang, W., J. Cheng, J. Allaire, C. Sievert, B. Schloerke, Y. Xie, J. Allen, J. McPherson, A. Dipert, B. Borges (2024). shiny: Web Application Framework for R. R package version 1.9.1, https://CRAN.R-project.org/package=shiny

3.Gu, Z. et al. “circlize Implements and Enhances Circular Visualization in R.” Bioinformatics, vol. 30, no. 19, 2014, pp. 2811–2812. doi:10.1093/bioinformatics/btu393.

4.Gu, Zuguang, Roland Eils, and Matthias Schlesner. “Complex Heatmaps Reveal Patterns and Correlations in Multidimensional Genomic Data.” Bioinformatics, vol. 32, no. 18, 2016, pp. 2847–2849. https://doi.org/10.1093/bioinformatics/btw313.

5.Lawrence, Michael, et al. “Software for Computing and Annotating Genomic Ranges.” PLoS Computational Biology, vol. 9, no. 8, 2013, e1003118. https://doi.org/10.1371/journal.pcbi.1003118.

6.Liao, Y., Gordon K. Smyth, and Wei Shi. “The R Package Rsubread is Easier, Faster, Cheaper and Better for Alignment and Quantification of RNA Sequencing Reads.” Nucleic Acids Research, vol. 47, no. 8, 2019, e47. doi:10.1093/nar/gkz114. Available at: https://academic.oup.com/nar/article/47/8/e47/5371636.

7.Morgan, M., P. Aboyoun, R. Gentleman, M. Lawrence, and H. Pages. “GenomicAlignments: Efficient Alignments Processing in R for NGS Data.” Bioconductor, 2019, doi:10.18129/B9.bioc.GenomicAlignments. Available at: https://bioconductor.org/packages/release/bioc/html/GenomicAlignments.html.

8.Morgan, Martin, Vincent Obenchain, James Hester, and Hervé Pagès. SummarizedExperiment: Summarized Experiment Container. R package version 1.28.0, Bioconductor, 2022, https://bioconductor.org/packages/SummarizedExperiment.

9.National Center for Biotechnology Information (NCBI). Saccharomyces cerevisiae S288C Genome Assembly (GCF_000146045.2). NCBI Datasets, https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_000146045.2/. Accessed 4 Nov. 2024.

10.National Center for Biotechnology Information (NCBI). Sequence Read Archive (SRA) Run: ERR12205202. NCBI SRA, https://trace.ncbi.nlm.nih.gov/Traces/?view=run_browser&acc=ERR12205202&display=download. Accessed 4 Nov. 2024.

11.National Center for Biotechnology Information (NCBI). Sequence Read Archive (SRA) Run: SRR29917898. NCBI SRA, https://trace.ncbi.nlm.nih.gov/Traces/?view=run_browser&acc=SRR29917898&display=download. Accessed 4 Nov. 2024.

12.OpenAI. ChatGPT: Assistance with R Function Development for Bioinformatics Applications, “LegitxMut”. https://chat.openai.com. Accessed 5 Nov. 2024.

13.Pagès, Hervé, Patrick Aboyoun, S. DebRoy, and Michael Lawrence. GenomeInfoDb: Utilities for Manipulating Chromosome Names, Including Modifying the Names to Follow a Particular Convention. R package version 1.36.0, Bioconductor, 2023, https://bioconductor.org/packages/GenomeInfoDb.

14.R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, 2024, Vienna, Austria, https://www.R-project.org/.

15.Silva, Anjali. TestingPackage. GitHub, https://github.com/anjalisilva/TestingPackage. Accessed 5 Nov. 2024.

16.Wickham, Hadley. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag, 2016, https://ggplot2.tidyverse.org.

17.Wickham, Hadley, et al. dplyr: A Grammar of Data Manipulation. R package version 1.1.2, 2023, https://CRAN.R-project.org/package=dplyr.

18.Wickham, H. stringr: Simple, Consistent Wrappers for Common String Operations. R package version 1.4.0, 2019, https://CRAN.R-project.org/package=stringr.

This package was developed as part of an assessment for 2024 BCB410H: Applied Bioinformatics course at the University of Toronto, Toronto, CANADA. LegitXMutwelcomes issues, enhancement requests, and other contributions. To submit an issue, use the GitHub issues.

The package may take a while to download, because it requires multiple dependencies. The workflow of this version of the package only supports the display of insertions and deletions(indel) mutation patterns due to the current implementation of the alignment function. However, the Manhattan plot visualization in this version can display single nucleotide polymorphisms(SNPs) when provided with appropriate input data.

The following figures were generating using the data set SRR29917898

The package tree structure is provided below.

- LegitXMut
  |- LegitXMut.Rproj
  |- DESCRIPTION
  |- NAMESPACE
  |- LICENSE
  |- README.md
  |- inst
    CITATION
    |- extdata
      |- ERR12205202.fastq
      |- aligned_output.bam
      |- aligned_output.bam.indel.vcf
      |- ERR12205202.fastq
      |- heatmap.png
      |- manhattan.png
      |- rainfall.png
      |- updated.vcf
      |- workflow.png
      |- yeast.fna
    |- shiny-scripts
      |- app.R
  |- man
    |- alignment_FASTQ.Rd
    |- update_vcf.Rd
    |- plot_vcf_mutation_data.Rd
    |- runLegitXMut.Rd
  |- R
    |- alignment_FASTQ.R
    |- update_vcf.R
    |- plot_vcf_mutation_data.R
    |- runLegitXMut.R
  |- vignettes
    |- heatmap.png
    |- manhattan.png
    |- rainfall.png
    |- Introduction_Of_LegitXMut.Rmd
  |- tests
    |- testthat.R
    |- testthat
      |- test-alignment_FASTQ.R
      |- test-update_vcf.R
      |- test-plot_vcf_mutation_data.R