ArticleGenome research2021
MAnorm2 for quantitatively comparing groups of ChIP-seq samples.
Article in Genome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed, 74 citations in OpenAlex.
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- Transcription factor ZNF263 primes human embryonic stem cells for pluripotency dissolution and lineage commitment.Nature communications · 2025Article
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- Replication program of a single-chromosome budding yeast strain.Nucleic acids research · 2025Article
- Selecting ChIP-seq normalization methods from the perspective of their technical conditions.Briefings in bioinformatics · 2025Article
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- IGN: Invariable gene set-based normalization for chromatin accessibility profile data analysis.Computational and structural biotechnology journal · 2025Article
- Accelerating Single-Cell Sequencing Data Analysis with SciDAP: A User-Friendly Approach.Methods in molecular biology (Clifton, N.J.) · 2025Article
- EAP: A versatile cloud-based platform for efficient quantitative analysis of large-scale ChIP/ATAC-seq datasets.Computational and structural biotechnology journal · 2025Article
- Short-term starvation inhibits CD36 N-glycosylation and downregulates USP7 UFMylation to alleviate RBPJ-maintained T cell exhaustion in liver cancer.Theranostics · 2025Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
Abstract
Eukaryotic gene transcription is regulated by a large cohort of chromatin-associated proteins, and inferring their differential binding sites between cellular contexts requires a rigorous comparison of the corresponding ChIP-seq data. We present MAnorm2, a new computational tool for quantitatively comparing groups of ChIP-seq samples. MAnorm2 uses a hierarchical strategy for normalization of ChIP-seq data and assesses within-group variability of ChIP-seq signals based on an empirical Bayes framework. In this framework, MAnorm2 allows for abundant differential ChIP-seq signals between groups of samples as well as very different global within-group variability between groups. Using a number of real ChIP-seq data sets, we observed that MAnorm2 clearly outperformed existing tools for differential ChIP-seq analysis, especially when the groups of samples being compared had distinct global within-group variability.
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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.