Ever wondered what M184V, K65R actually mean? I learnt it from rebuilding Stanford’s HIV resistance algorithm from scratch to find out. Spoiler: it took tons of code to match their 3-line tool. But the lesson was worth it
Learned RNA-seq workflow using C. difficile data from a published study 🧬. Processed raw reads through fastp → kallisto → DESeq2 -> GSEA pipeline. Results matched the original paper’s findings, with clear differential expression between mucus and control conditions 📊.
Ever wondered how DNA alignment actually works under the hood? 🧬 We coded the Needleman-Wunsch algorithm from scratch, working through scoring matrices by hand with simple examples like “CAT” vs “CT” before testing on real E. coli sequences. Pretty neat to see the magic happen! ✨
🧬🔬 Explore phylogenetic analysis from genome to tree! Basic workflow with R/Bioconductor. Learnt to work with large genomic dataset. Extract 16S rRNA from 10K+ E.coli strains using dataset dehydrate, barrnap for extraction, rapidNJ for tree building & FigTree for visualization.
Instead of flashcards, we Rube Goldberg’d this with Bioconductor! Analyzed 3,280 E. coli genomes from NCBI, detecting ESBL genes in 84.4% of samples. CTX-M-15 was most common. Helped us understand gene nomenclature and sequence analysis! 📊🔬