While R has several libraries that nicely visualize GO Enrichment results, Python does not. This article covers how to create similar plots in Python, from basic bar and dot plots to semantic similarity-based heatmaps, MDS scatter plots, networks, and treemaps.
A summary of information and tools related to each step of phylogenetic analysis: Alignment, Trimming, Model Selection, and Tree Construction
Cell Ranger is a tool that anyone familiar with single cell RNA-seq will know. I had never used it before, but decided to give it a try. However, it internally uses STAR for mapping, and there is a problem (that nobody else seems to mind) where you cannot pass STAR parameters as arguments. The official answer is to build it yourself, though they take no responsibility for it.
GATK4 is a time-consuming tool, but with enough compute power you can speed it up using split intervals. This post summarizes how to work with interval lists.
The RNA-seq variant calling pipeline differs slightly from the genomic sequence pipeline. This post documents how to run the best practice workflow in bash.
Deep learning has achieved remarkable results in natural language processing. For predicting protein function through GO Term annotation from amino acid sequences, homology searches such as BLAST have traditionally been the dominant approach. Recently, several tools have begun performing function prediction using deep learning. In this post, we try out DeepGOPlus.
GO analysis is a widely used analytical method, but to understand it properly you first need to understand GO itself. This post covers the fundamentals of GO Terms.
Notes on tools and data structures for performing queries on interval data
Protein-based phylogenetic analysis is a well-known and important method for studying gene function and evolution. In this post, we create a multiple alignment using MUSCLE, remove non-conserved regions with trimAl, and then perform phylogenetic analysis using the maximum likelihood method with RAxML.
Reading and writing fastq/fastq.gz files using rust-bio.