ArticlePLoS computational biology2013
Practical guidelines for the comprehensive analysis of ChIP-seq data.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
137 citing papers in PubMed, 1 synthesis or guideline pooled it.
- ChIP-Hub provides an integrative platform for exploring plant regulome.Nature communications · 2022Pooled it
- ComprehensiveNon-coding RNA · 2026Article
- EpGAT: integrating epigenetics and 3D genome structure to predict alternative splicing and polyadenylation.Briefings in bioinformatics · 2026Article
- Beyond blacklists: a critical assessment of exclusion set generation strategies and alternative approaches.Bioinformatics (Oxford, England) · 2026Article
- Many roads lead to a plant cistrome: mapping and interpreting transcription factor binding in plants.Genome biology · 2026Review
- A Statistical Framework for Measuring Reproducibility and Replicability of High-Throughput Experiments From Multiple Sources.Statistics in medicine · 2026Article
- Methods for the Investigation of Protein-Ligands Interactions.Advances in experimental medicine and biology · 2026Review
- SNAP: Streamlined Nextflow Analysis Pipeline for Immunoprecipitation-Based Epigenomic Profiling of Circulating Chromatin.bioRxiv : the preprint server for biology · 2025Article
- Modeling post-gastrula development via bidirectional pluripotent stem cells.Cell research · 2025Article
- Beyond Blacklists: A Critical Assessment of Exclusion Set Generation Strategies and Alternative Approaches.bioRxiv : the preprint server for biology · 2025Article
- ThebioRxiv : the preprint server for biology · 2025Article
- Genotype inference from aggregated chromatin accessibility data reveals genetic regulatory mechanisms.Genome biology · 2025Article
- A Joint Analysis of RNA-DNA and DNA-DNA Interactomes Reveals Their Strong Association.International journal of molecular sciences · 2025Article
- Article
- Acetylation-Mediated Epigenetic Consequences for Biological Control and Cancer.Results and problems in cell differentiation · 2025Review
- Characterization of the Cannabis sativa glandular trichome epigenome.BMC plant biology · 2024Article
- Advances in omics data for eosinophilic esophagitis: moving towards multi-omics analyses.Journal of gastroenterology · 2024Review
- DNA breathing integration with deep learning foundational model advances genome-wide binding prediction of human transcription factors.Nucleic acids research · 2024Article
- Genotype inference from aggregated chromatin accessibility data reveals genetic regulatory mechanisms.bioRxiv : the preprint server for biology · 2024Article
- Biostatistical Aspects of Whole Genome Sequencing Studies: Preprocessing and Quality Control.Biometrical journal. Biometrische Zeitschrift · 2024Article
77 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Mapping the chromosomal locations of transcription factors, nucleosomes, histone modifications, chromatin remodeling enzymes, chaperones, and polymerases is one of the key tasks of modern biology, as evidenced by the Encyclopedia of DNA Elements (ENCODE) Project. To this end, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the standard methodology. Mapping such protein-DNA interactions in vivo using ChIP-seq presents multiple challenges not only in sample preparation and sequencing but also for computational analysis. Here, we present step-by-step guidelines for the computational analysis of ChIP-seq data. We address all the major steps in the analysis of ChIP-seq data: sequencing depth selection, quality checking, mapping, data normalization, assessment of reproducibility, peak calling, differential binding analysis, controlling the false discovery rate, peak annotation, visualization, and motif analysis. At each step in our guidelines we discuss some of the software tools most frequently used. We also highlight the challenges and problems associated with each step in ChIP-seq data analysis. We present a concise workflow for the analysis of ChIP-seq data in Figure 1 that complements and expands on the recommendations of the ENCODE and modENCODE projects. Each step in the workflow is described in detail in the following sections.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.