CleanIt: Per-sample RNA-seq processing outputs for trimming impact analysis

Full per-sample HPC outputs from the CleanIt project, which evaluates whether read trimming is necessary for standard Illumina RNA-seq differential expression workflows. Contains featureCounts gene-level counts, Bowtie2 alignment statistics, raw FastQC reports, Trimmomatic read survival logs, per-stage pipeline timings, and leave-one-sample-out (LOSO) concordance results for approximately 1,155 SRRs across 48 BioProjects, each processed under 6 trimming conditions (untrimmed, adapter-only, P5, P10, P20, P35). Scripts and analysis notebooks are available at: https://github.com/jallmer/cleanit Archive contents: - cleanit_counts.tar.gz — Gene-level featureCounts output per SRR per trimming mode - cleanit_bowtie2_stats.tar.gz — Bowtie2 alignment statistics per SRR - cleanit_fastqc_raw.tar.gz — Raw FastQC reports (HTML + ZIP) per SRR - cleanit_trimmomatic_stats.tar.gz — Trimmomatic read survival statistics per SRR - cleanit_timings.tar.gz — Per-stage pipeline timings per SRR - cleanit_concordance.tar.gz — LOSO DE/GSEA concordance results per BioProject