seqkit
fasql
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seqkit
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A look at the Mojo language for bioinformatics
I've been thinking to learn Rust for these use cases, but always get frustrated with the complexity.
I find Go is a great middle-ground though! And now there starts to be a few more bio-related tools and toolkits out there, including:
- https://github.com/vertgenlab/gonomics
- https://github.com/biogo/biogo
- https://github.com/shenwei356/bio
... except from there being some really popular bio tools written in Go, like:
- https://github.com/shenwei356/seqkit
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Help with understanding awk code
You could also check out tools specialized for FASTA processing like https://github.com/shenwei356/seqkit and https://github.com/lh3/seqtk
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What are some good examples of well-engineered bioinformatics pipelines?
Seqkit - thoroughly maintained with extensive tutorials and benchmarking info - https://github.com/shenwei356/seqkit
fasql
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Training resources for Biopython?
Shameless self promotion, but my company released an open source library that reads fasta and fastq files in python or other languages... https://github.com/wheretrue/fasql -- obv biased, but it's faster than biopython and has a lower footprint when you just need that.
- Show r/bioinformatics: fasql, a way to run SQL queries on FASTA and FASTQ files
What are some alternatives?
seqtk - Toolkit for processing sequences in FASTA/Q formats
fastp - An ultra-fast all-in-one FASTQ preprocessor (QC/adapters/trimming/filtering/splitting/merging...)
sage - Proteomics search & quantification so fast that it feels like magic
h3-duckdb - Bindings for H3 to DuckDB
rush - A cross-platform command-line tool for executing jobs in parallel
readfq - Fast multi-line FASTA/Q reader in several programming languages
rnaseq - RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.
juicer - A One-Click System for Analyzing Loop-Resolution Hi-C Experiments
spades - SPAdes Genome Assembler
gatk4-genome-processing-pipeline-azure - Workflows used for processing whole genome sequence data + germline variant calling.