Claude-skill-registry-data bio-epitranscriptomics-merip-preprocessing
Align and QC MeRIP-seq IP and input samples for m6A analysis. Use when preparing MeRIP-seq data for peak calling or differential methylation analysis.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry-data
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry-data "$T" && mkdir -p ~/.claude/skills && cp -r "$T/data/merip-preprocessing" ~/.claude/skills/majiayu000-claude-skill-registry-data-bio-epitranscriptomics-merip-preprocessing && rm -rf "$T"
manifest:
data/merip-preprocessing/SKILL.mdsource content
MeRIP-seq Preprocessing
Alignment with STAR
# Build index (once) STAR --runMode genomeGenerate \ --genomeDir star_index \ --genomeFastaFiles genome.fa \ --sjdbGTFfile genes.gtf # Align IP and input samples for sample in IP_rep1 IP_rep2 Input_rep1 Input_rep2; do STAR --genomeDir star_index \ --readFilesIn ${sample}_R1.fastq.gz ${sample}_R2.fastq.gz \ --readFilesCommand zcat \ --outSAMtype BAM SortedByCoordinate \ --outFileNamePrefix ${sample}_ done
QC Metrics
# Index BAMs for bam in *Aligned.sortedByCoord.out.bam; do samtools index $bam done # Check IP enrichment # Good MeRIP: IP should have peaks, input should be uniform samtools flagstat IP_rep1_Aligned.sortedByCoord.out.bam
IP/Input Correlation
import deeptools.plotCorrelation as pc # Check replicate correlation multiBamSummary bins \ -b IP_rep1.bam IP_rep2.bam Input_rep1.bam Input_rep2.bam \ -o results.npz plotCorrelation -in results.npz \ --corMethod spearman \ -o correlation.png
Related Skills
- read-qc - Raw read quality assessment
- read-alignment - General alignment concepts
- m6a-peak-calling - Next step after preprocessing