bio-chipseq-allele-specific-binding
Detects allele-specific transcription factor or histone modification binding from heterozygous-variant ChIP-seq using WASP (reference-bias filter; mandatory upstream), RASQUAL (joint QTL + bias-corrected testing), BaalChIP (Bayesian beta-binomial with copy-number-aware overdispersion), and AlleleSeq (personalized diploid genome). Handles imprinted-locus awareness, X-inactivation artifacts, cancer copy-number imbalance, and integration with downstream caQTL / bQTL mapping. Use when identifying variants with allelic effects on TF binding, fine-mapping causal regulatory variants, validating deep-
npx skills add BioTender-max/awesome-bio-agent-skills --skill allele-specific-binding --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: WASP 0.3.4+, RASQUAL 1.1+, BaalChIP 1.30+ (Bioconductor), AlleleSeq 2.0+, samtools 1.19+, bcftools 1.19+, GATK 4.5+, pysam 0.22+. # Allele-Specific Binding (ASB) **"Identify variants that affect transcription factor or histone modification binding in cis"** -> Compare ChIP-seq read counts at the reference and alternate alleles of heterozygous variants in a single sample. Differential read counts (ALT vs REF at hetSNPs in peaks) reveal allele-specific binding. - CLI (mandatory bias filter): WASP `mapping pipeline` to remove reference-allele mapping bias - CLI (joint association): RASQUAL with `--n-permutations` for cis-QTL + ASB - R (Bayesian beta-binomial): BaalChIP with copy-number-aware overdispersion - CLI (personalized genome): AlleleSeq with phased diploid genome - Statistical test: beta-binomial likelihood ratio or chi-squared on count tables ASB analysis has three universal pitfalls: reference-allele mapping bias (universal across short-read aligners), imprinted loci (constitutively allele-skewed by biology), and copy-number variation (changes effective allele dose). All three must be addressed or results are unreliabl
- Version Compatibility
- Method Taxonomy
- Universal First Step: WASP Reference-Bias Filter
- Workflow: BaalChIP (Recommended for Cancer / Copy-Number-Imbalanced Samples)
- Workflow: RASQUAL (Joint cis-QTL + ASB)
- Workflow: AlleleSeq (Personalized Diploid Genome)
- Three Universal Pitfalls
- Pitfall 1: Imprinted Loci Are Constitutively Skewed
- Pitfall 2: X-Inactivation in Females
- Pitfall 3: Copy-Number Imbalance (Cancer Genomes)
- Per-Tool Failure Modes
- WASP -- Reference panel mismatch
- WASP -- Excessive read loss
- RASQUAL -- Convergence failure
WASP mapping pipeline bowtie2 -x hg38 -1 R1.fq -2 R2.fq -S step1.sam samtools view -bS step1.sam | samtools sort -o step1.bam samtools index step1.bam python /path/to/WASP/mapping/find_intersecting_snps.py \ step1.bam bowtie2 -x hg38 -1 wasp_out/step1.remap.fq.gz -S step2.sam python /path/to/WASP/mapping/filter_remapped_reads.py \ step1.to.remap.bam step2.bam step1.keep.bam samtools sort -o step1.wasp.bam step1.keep.bam
What does the bio-chipseq-allele-specific-binding skill do?
Detects allele-specific transcription factor or histone modification binding from heterozygous-variant ChIP-seq using WASP (reference-bias filter; mandatory upstream), RASQUAL (joint QTL + bias-corrected testing), BaalChIP (Bayesian beta-binomial with copy-number-aware overdispersion), and AlleleSeq (personalized diploid genome). Handles imprinted-locus awareness, X-inactivation artifacts, cancer copy-number imbalance, and integration with downstream caQTL / bQTL mapping. Use when identifying variants with allelic effects on TF binding, fine-mapping causal regulatory variants, validating deep-
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill allele-specific-binding --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.