Módszerek összehasonlítása

	Differenciális ChIP-seq csúcshívás	Variánsdetektálás
Tudományterület	Bioinformatika	Bioinformatika
Módszercsalád	Process / pipeline	Process / pipeline
Keletkezés éve	2011-2012	2009–2010 (modern high-throughput era)
Megalkotó	Rory Stark and Gordon Brown (DiffBind framework); broader ENCODE community	Li et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010)
Típus	Comparative genomic signal analysis pipeline	Computational genomics pipeline
Alapmű	Ross-Innes, C. S., Stark, R., Teschendorff, A. E., Holmes, K. A., Ali, H. R., Dunning, M. J., Brown, G. D., Gojis, O., Ellis, I. O., Green, A. R., Ali, S., Chin, S. F., Palmieri, C., Caldas, C., & Carroll, J. S. (2012). Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature, 481(7381), 389-393.	McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., ... & DePristo, M. A. (2010). The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research, 20(9), 1297–1303.
Alternatív nevek	differential ChIP-seq, ChIP-seq differential binding analysis, comparative peak calling, differential chromatin occupancy analysis	SNP calling, genotyping from sequencing, mutation detection, variant detection
Kapcsolódó	6	6
Összefoglaló	Differential ChIP-seq peak calling identifies genomic loci where a protein of interest — typically a transcription factor or histone mark — shows significantly altered binding or occupancy between two or more biological conditions. By combining standard ChIP-seq peak detection with count-based statistical testing, the method reveals condition-specific regulatory elements, providing a genome-wide map of dynamic chromatin interactions underlying cellular state changes.	Variant calling is the computational process of identifying positions in a sequenced genome that differ from a reference sequence — including single nucleotide polymorphisms (SNPs), small insertions and deletions (indels), and structural variants. It transforms aligned sequencing reads into an interpretable catalogue of genetic differences, forming the foundation for population genetics, disease-gene discovery, and clinical genomics applications.