Posted on Wed 13 May 2026 in commentary • Tagged with sysadmin, git, microsoft, open-source
TLDR - I moved most of my github presence to codeberg. Including this page, my personal/professional website: https://groverj3.codeberg.page.
This is mostly just going to be a ramble. But probably not a very long one.
When I was in graduate school, pushing code to Github was a highly …
Posted on Fri 26 April 2024 in commentary • Tagged with workflows, bioinformatics
Since I was in grad school I've been writing bioinformatics workflows. Usually to process NGS data. The concept of a workflow is simple, and not limited to the domain of bioinformatics. However, a workflow (aka "pipeline") used to analyze data from next generation sequencing (again, will it ever be "current …
Posted on Sat 30 May 2020 in commentary • Tagged with grad school, jobs
I started this github site as a place to expand my professional reach by posting my random musings on bioinformatics, Linux, data science, and etc. I made a few reasonably cogent posts, but then life got in the way! It's been a really busy time, a very eventful year. I'm …
Posted on Thu 22 August 2019 in commentary • Tagged with bioinformatics, python, workflows
In contrast to the zen of python there are actually many ways to handle sequence data in Python. There are several packages on PyPI that provide parsers for sequence formats like .fastq and .fasta. I've never bothered with these, including the oft-used Biopython. I vaguely remembered Biopython being slower than …
Posted on Fri 09 August 2019 in commentary • Tagged with bioinformatics, thoughts, workflows
Bioinformatic analyses often require lengthy workflows or pipleines, where the output of program A feeds into program B, and so on. These programs may also not output their results in a format which is convenient to use in the subsequent steps, requiring writing a conversion script, or piping its output …
Posted on Tue 09 July 2019 in commentary • Tagged with bioinformatics, thoughts, rnaseq, workflows
When analyzing RNAseq you're faced with many possible analysis pipelines. The biggest decision you need to make is what the purpose of your experiment is. I will make the assumption that most of the time people want to determine which genes are differentially expressed between two samples, genotypes, conditions, etc …