القائمة
RNA-seq-specific alignment quality assessment using RSeQC and Qualimap for gene body coverage, strandedness, and rRNA contamination.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Decision-grade enzyme/protein mutation design for thermostability with bioactivity-preserving constraints enforced by default, plus structure-aware and consensus-ranking workflows.
Create or update repository skills that conform to local templates, provider metadata requirements, registry rules, and validation workflows.
Assess data quality by reporting missing values, outliers, sample size, and variance structure for each variable in a table.
Estimate model parameters using Bayesian inference (MCMC via Stan or PyMC), returning posterior distributions and credible intervals.
Cluster samples or features using k-means or hierarchical clustering, evaluate cluster quality with silhouette scores, and produce a dendrogram or cluster plot.
Compare a continuous variable between two groups with automatic selection of t-test, Welch test, or Mann-Whitney U test based on data properties.
| name | rnaseq-alignment-qc |
| description | RNA-seq-specific alignment quality assessment using RSeQC and Qualimap for gene body coverage, strandedness, and rRNA contamination. |
.bam + .bai)./alignment_qc_output)infer_experiment.py to determine library strandedness.geneBody_coverage.py for 5'-to-3' coverage profile across gene bodies.read_distribution.py for read distribution across genomic features (CDS, UTR, intron, intergenic).inner_distance.py for insert size distribution (paired-end data).rnaseq for comprehensive RNA-seq QC metrics.