ArticleGenome biology2022
Comprehensive assessment of differential ChIP-seq tools guides optimal algorithm selection.
Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Integrative Epigenomics: Bioinformatics Strategies for Multi-Omics Data Analysis in Health and Disease.Epigenomes · 2026Review
- An epigenomic investigation of atrial fibrillation in a matched left and right atrial human cohort.Clinical epigenetics · 2026Article
- A semidominant point mutation of Mediator tail subunit MED5b in Arabidopsis leads to altered enrichment of H3K27me3 and reduced expression of targets of MYC2.G3 (Bethesda, Md.) · 2025Article
- Evaluating the Performance of Peak Calling Algorithms Available for Intracellular G-Quadruplex Sequencing.International journal of molecular sciences · 2025Article
- ChIP-mini: a low-input ChIP-exo protocol for elucidating DNA-binding protein dynamics in intracellular pathogens.Nucleic acids research · 2025Article
- ChIP-Rx: Arabidopsis Chromatin Profiling Using Quantitative ChIP-Seq.Methods in molecular biology (Clifton, N.J.) · 2025Article
- The Evolution of Next-Generation Sequencing Technologies.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Best practices for differential accessibility analysis in single-cell epigenomics.Nature communications · 2024Article
- Enricherator: A Bayesian Method for Inferring Regularized Genome-wide Enrichments from Sequencing Count Data.Journal of molecular biology · 2024Article
- guidedNOMe-seq quantifies chromatin states at single allele resolution for hundreds of custom regions in parallel.BMC genomics · 2024Article
- TFscope: systematic analysis of the sequence features involved in the binding preferences of transcription factors.Genome biology · 2024Article
- MUFFIN: a suite of tools for the analysis of functional sequencing data.NAR genomics and bioinformatics · 2024Article
- Differential Analysis of Protein-DNA Binding Using ChIP-Seq Data.Methods in molecular biology (Clifton, N.J.) · 2024Article
- The Fgf/Erf/NCoR1/2 repressive axis controls trophoblast cell fate.Nature communications · 2023Article
- CSSQ: a ChIP-seq signal quantifier pipeline.Frontiers in cell and developmental biology · 2023Article
- Motif elucidation in ChIP-seq datasets with a knockout control.Bioinformatics advances · 2023Article
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2 authors.
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Abstract
backgroundThe analysis of chromatin binding patterns of proteins in different biological states is a main application of chromatin immunoprecipitation followed by sequencing (ChIP-seq). A large number of algorithms and computational tools for quantitative comparison of ChIP-seq datasets exist, but their performance is strongly dependent on the parameters of the biological system under investigation. Thus, a systematic assessment of available computational tools for differential ChIP-seq analysis is required to guide the optimal selection of analysis tools based on the present biological scenario.
resultsWe created standardized reference datasets by in silico simulation and sub-sampling of genuine ChIP-seq data to represent different biological scenarios and binding profiles. Using these data, we evaluated the performance of 33 computational tools and approaches for differential ChIP-seq analysis. Tool performance was strongly dependent on peak size and shape as well as on the scenario of biological regulation.
conclusionsOur analysis provides unbiased guidelines for the optimized choice of software tools in differential ChIP-seq analysis.
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