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.md
source 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