Merip preprocessing
Skill BioTender-max/awesome-bio-agent-skills/skills/bioskills/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.From its SKILL.md
npx -y skills add BioTender-max/awesome-bio-agent-skills --skill merip-preprocessingAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
2.5 KB, 579 tokens by cl100k_base, as published. Nobody here has run it
Version Compatibility
Reference examples tested with: STAR 2.7.11+, deepTools 3.5+, samtools 1.19+
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package>thenhelp(module.function)to check signatures - CLI:
<tool> --versionthen<tool> --helpto confirm flags
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
MeRIP-seq Preprocessing
"Preprocess my MeRIP-seq IP and input samples" → Align and QC methylated RNA immunoprecipitation sequencing data, comparing IP enrichment to input for downstream m6A peak calling.
- CLI:
STARfor splice-aware alignment,samtoolsfor post-processing,deepToolsfor QC
Alignment with STAR
Goal: Align MeRIP-seq IP and input samples to the genome with splice-aware mapping for downstream peak calling.
Approach: Build a STAR genome index with gene annotations, then loop through all IP and input samples to produce coordinate-sorted BAM files.
# 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/quality-reports - Raw read quality assessment
- read-alignment/star-alignment - General alignment concepts
- m6a-peak-calling - Next step after preprocessing
What ships with it: 3 files
4.4 KB alongside SKILL.md, 2 of them executable
examples/
- align_merip.shruns975 B
- merip_qc.pyruns2.5 KB
- usage-guide.md1.0 KB