What problem does it solve? Analyzing QuantStudio qPCR exports requires tedious manual steps: parsing TSV files, mapping 96-well layouts onto 384-well plates, averaging technical replicates correctly, and computing ΔCT/ΔΔCT statistics without inflating significance. This Skill guides an interactive, statistically sound workflow that produces a self-contained Quarto analysis notebook. ## Core Features & Use Cases - QuantStudio TSV Loading & Layout Mapping: Parses tab-separated exports (handling BOM headers and junk wells) and expands 96-well plate layouts into 384-well matrices with bad-well exclusion. - Diagnostic Visualizations: Generates CT heatmaps and annotated plate layout figures with dual 96/384-well coordinates, saved as PDFs. - Rigorous Statistics: Averages technical replicates before testing, applies housekeeping gene dropout filters, computes ΔCT/ΔΔCT/RQ, and runs Z-score significance tests with Benjamini-Hochberg FDR correction per gene. - Use Case: A researcher exports a QuantStudio run comparing gene expression across treated and control cell lines, then uses this Skill to verify the plate layout, filter samples with GAPDH dropout, and produce log₂ RQ bar plots annotated with p-values and FDR significance stars. ## Quick Start Use the qpcr-analysis skill to analyze my QuantStudio export at /data/experiment.tsv and build a Quarto notebook with ΔΔCT statistics and RQ plots.
