An overview of my bioinformatics projects with links to relevant pages and posts
A suite of Python scripts and modules for working with Oxford Nanopore Technologies long read sequencing data. All are available through pip and bioconda, see the README files on GitHub for further instructions.
Create plots from reads (fastq), alignments (bam) and albacore summary files. See also this gallery for examples.
Compare multiple sequencing runs or datasets for read length, quality, accuracy, and throughput.
Trim and filter reads (while streaming) on length and quality.
See also this blog post. Optionally takes an albacore summary file to perform faster and more accurate filtering, see this post.
Performs fast extraction of statistics from reads (fastq), alignments (bam) and albacore summary files.
Investigates and plots sequence composition and quality at read ends similar to FastQC.
A command-line R script for convenient and reproducible differential expression analysis using the DESeq2, edgeR and limma-voom algorithms. The script is available on GitHub. It also performs counting using featureCounts or takes counts as prepared by Salmon. Appropriate plots and various output tables with results and normalized counts are produced. A bash script for creating a test dataset is also available.