RNA-seq Transcript Quantification Workflow
Built a reproducible RNA-seq workflow in Snakemake with reference-guided analysis using STAR and featureCounts, plus de novo transcript quantification with Trinity, Kallisto, and RSEM.
Computational projects that demonstrate my foundation in genomic data analysis, workflow engineering, reproducibility, and scientific software development as I build toward machine learning research in biology.
Built a reproducible RNA-seq workflow in Snakemake with reference-guided analysis using STAR and featureCounts, plus de novo transcript quantification with Trinity, Kallisto, and RSEM.
Built a Snakemake workflow for bacterial whole-genome sequencing analysis, including QC, short-read or hybrid assembly, polishing, annotation, core-genome phylogeny, and optional MLST, AMR, virulence, and plasmid screening.
Designed and implemented a Nextflow DSL2 workflow to recover RNA-seq reads with visible poly(A)/poly(T) tail signal, trim the tail sequence, and realign the mRNA-derived read body to a reference genome.
Built a Snakemake pipeline for Human Adenovirus genome assembly, comparative genomics, and phylogenetic analysis, from raw paired-end reads through QC, assembly, scaffolding, consensus calling, variability plots, and tree generation.