star-aligner

RNA-seq analysis from FASTQ to biology: STAR alignment, gene-level counts, DESeq2 differential expression, and GO/KEGG/GSEA. Metadata-driven design with human/mouse/rat support.

A modular, containerized NGS pipeline for RNA-seq, long-read, and metagenomic analysis

Immunopeptidogenomics pipeline that builds a cryptic peptide database from RNA-seq and identifies non-canonical (cryptic) peptides in immunopeptidomics mass spectrometry data.

Empirical benchmark suite comparing execution times, peak RAM usage, and cloud compute costs across RNA-Seq aligners, single-cell frameworks, and variant callers.

Modular RNA-seq variant calling and annotation framework (hg38) integrating STAR and GATK Best Practices to extract high-confidence SNPs and enable gene-level and systems biology analyses of expressed genetic variation.

The workflow is executed with `ww-rnaseq.wdl` through Cromwell and SLURM. It performs read QC, adapter trimming, STAR alignment, RSeQC alignment QC, count assembly, DESeq2 analysis, and MultiQC reporting.

A reproducible RNA-seq analysis pipeline built with Nextflow and Docker, supporting QC, alignment, quantification, differential expression, transcript discovery, and automated reporting.

RNA-seq QC benchmark (custom Python vs FastQC), adapter trimming, STAR alignment, and htseq-count-based strand-specificity analysis

Automated RNA-seq reference builder for STAR and Salmon. Features container-aware memory detection, automatic Ensembl/GENCODE downloads, and version-controlled index generation.

Parallel end-to-end bulk RNA-seq pipeline on a PBS/HPC job array: FastQC, Trimmomatic, STAR alignment, and featureCounts, with a Bioconda setup script.

RNA-Sequencing

Differential gene expression analysis for samples with replicates using STAR-DeSeq2 pipeline

Two-phase RNA-seq differential expression pipeline (Drosophila → human) built from scratch on laptop and HPC, with real debugging and validation.”

Independently maintained, performance-oriented successor to the STAR RNA-seq aligner

End-to-end RNA-seq pipeline for BRCA tumor vs normal differential expression analysis

Optimized RNA-seq quantification pipelines (Salmon, STAR+Salmon, pyDESeq2, METAFlux) validated against a CLC Genomics Workbench baseline

End-to-end RNA-seq differential expression analysis workflow for RUNX3 knockout gastric cancer cells using STAR, MultiQC, featureCounts and DESeq2.

counting Insertion (I), deletion (D), splcing(N) events from CIGAR string in sam file generated by STAR aligner

Bulk RNA-seq pipeline: transcriptional characterization of anti-PD1 responders vs non-responders in metastatic melanoma