The protein database search engine analysis for a typical quantitative proteomics experiment yields a matrix of rows (identified protein groups) and columns (conditions; healthy and diseased, time-series or immunoprecipitation experiments, and so on). The downstream analysis often includes data quality assessment and statistical analysis (to identify differentially expressed proteins). Furthermore, machine learning and functional analysis are used for biological interpretations and hypothesis generation. This repository (work in progress) will host a collection of R scripts used in proteomics and/or omics data analysis that will help in the preliminary assessment of the datasets. Briefly, this repo can help in identifying patterns and inconsistencies associated with the dataset and is used at various phases of the data analysis process. Each folder includes the following files to regenerate specific plots.
- R script
- Data frame template
- Figure
These files will enable an intuitive graphical representation of the complex biological data.
Coefficient of variation (CV) plot: R script for creating a CV plot with proteomics data.
The original code was modified from the r-graph-gallery scatter plot chart type to plot CV graph.
Volcano plot: R script for creating a volcano plot with proteomics data. The data used here was adapted from our publication related to COVID-19 study.
The code was adopted from the EnhancedVolcano repository. This repository is an excellent resource for plotting the volcano plot and adding complex features to make it more informative.
Heatmap: pheatmap package was used to create heatmap. The data used for making the heatmap was derived from our publication of COVID-19 study.
Following nice blogs, I referred to put together a code.
- pheatmap: create annotated heatmaps in R (detailed guide)
- Making a heatmap in R with the pheatmap package
Barplot: R script for creating a bar chart with omics data. This analysis used in-house proteomics data to generate the bar plot with error bars to assess the precise measurement.
RankPlot: R script for creating a protein rank abundance curve.
BoxPlot: R script used for creating box plots. This graph helps in elucidating the distribution of expression values for proteins (in this case coefficient of variation values associated with different LC-MS/MS gradients.
The data used for generating box plot, rank plot and CV plot was derived from our Astral preprint.