Hello Bioinformatics lovers,

Welcome, new subscribers. My mission is to help you to learn computational skills.

5 papers all computational biologists should read:

1. ​A Quick Guide to Organizing Computational Biology Projects ​
2. ​Ten Simple Rules for Reproducible Computational Research​
3. ​Ten simple rules for biologists learning to program ​
4. ​Good enough practices in scientific computing​
5. ​Best Practices for Scientific Computing

Other resources I found useful this week:

1. A new tool for doing gene set enrichment analysis for single-cell data borch.dev/uploads/screpertoire/articles/running_escape​
2. ​My old video on the differences between bioinformatics and computational biology
3. Two resources for cloud computing: Google cloud for bioinformatics https://github.com/lynnlangit/gcp-for-bioinformatics​
4. AWS for bioinformatics https://github.com/lynnlangit/aws-for-bioinformatics​
5. A post from my friend Dean Lee What to expect in a biotech/pharma compbio interview​
6. ​nf-core/airrflow: an adaptive immune receptor repertoire analysis workflow employing the Immcantation framework​
7. Genomics intervals are everywhere, learn how to deal with them using bedtools (This is a must-have in your tool kits)https://bedtools.readthedocs.io/en/latest/index.html and this one https://github.com/noamteyssier/bedrs, in R you use GenomicsRanges package.
8. ​Single-cell allele-specific expression analysis reveals dynamic and cell-type-specific regulatory effects​

Happy Learning!

Tommy

DNA confesses Data speak

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