ArticleBriefings in bioinformatics2016
A comprehensive comparison of tools for differential ChIP-seq analysis.
Article in Briefings in bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
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Who cites it
54 citing papers in PubMed.
- Selecting ChIP-seq normalization methods from the perspective of their technical conditions.Briefings in bioinformatics · 2025Article
- Annotation of cis-regulatory-associated histone modifications in the genomes of two Thoroughbred stallions.Frontiers in genetics · 2025Article
- HJURP is recruited to double-strand break sites and facilitates DNA repair by promoting chromatin reorganization.Oncogene · 2024Article
- Analyzing histone ChIP-seq data with a bin-based probability of being signal.PLoS computational biology · 2023Article
- Cell-specific and shared regulatory elements control a multigene locus active in mammary and salivary glands.Nature communications · 2023Article
- Getting personal with epigenetics: towards individual-specific epigenomic imputation with machine learning.Nature communications · 2023Article
- 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
- Rare diseases of epigenetic origin: Challenges and opportunities.Frontiers in genetics · 2023Review
- Exploitation of epigenetic variation of crop wild relatives for crop improvement and agrobiodiversity preservation.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Review
- DiffChIPL: a differential peak analysis method for high-throughput sequencing data with biological replicates based on limma.Bioinformatics (Oxford, England) · 2022Article
- Efficient detection and classification of epigenomic changes under multiple conditions.Biometrics · 2022Article
- Comprehensive assessment of differential ChIP-seq tools guides optimal algorithm selection.Genome biology · 2022Article
- HyperChIP: identification of hypervariable signals across ChIP-seq or ATAC-seq samples.Genome biology · 2022Article
- SEAseq: a portable and cloud-based chromatin occupancy analysis suite.BMC bioinformatics · 2022Article
- ChIP-AP: an integrated analysis pipeline for unbiased ChIP-seq analysis.Briefings in bioinformatics · 2022Article
- Differential H3K9me2 heterochromatin levels and concordant mRNA expression in postmortem brain tissue of individuals with schizophrenia, bipolar, and controls.Frontiers in psychiatry · 2022Article
- Bioinformatics Methods for ChIP-seq Histone Analysis.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Recent Bioinformatic Progress to Identify Epigenetic Changes Associated to Transposable Elements.Frontiers in genetics · 2022Review
- Differential ATAC-seq and ChIP-seq peak detection using ROTS.NAR genomics and bioinformatics · 2021Article
Corrections and comments
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
ChIP-seq has become a widely adopted genomic assay in recent years to determine binding sites for transcription factors or enrichments for specific histone modifications. Beside detection of enriched or bound regions, an important question is to determine differences between conditions. While this is a common analysis for gene expression, for which a large number of computational approaches have been validated, the same question for ChIP-seq is particularly challenging owing to the complexity of ChIP-seq data in terms of noisiness and variability. Many different tools have been developed and published in recent years. However, a comprehensive comparison and review of these tools is still missing. Here, we have reviewed 14 tools, which have been developed to determine differential enrichment between two conditions. They differ in their algorithmic setups, and also in the range of applicability. Hence, we have benchmarked these tools on real data sets for transcription factors and histone modifications, as well as on simulated data sets to quantitatively evaluate their performance. Overall, there is a great variety in the type of signal detected by these tools with a surprisingly low level of agreement. Depending on the type of analysis performed, the choice of method will crucially impact the outcome.
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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.