ArticleProceedings of the National Academy of Sciences of the United States of America2013
Differential principal component analysis of ChIP-seq.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- The Rayleigh Quotient and Contrastive Principal Component Analysis I.bioRxiv : the preprint server for biology · 2025Article
- scStateDynamics: deciphering the drug-responsive tumor cell state dynamics by modeling single-cell level expression changes.Genome biology · 2024Article
- A framework for group-wise summarization and comparison of chromatin state annotations.Bioinformatics (Oxford, England) · 2023Article
- Computational methods to explore chromatin state dynamics.Briefings in bioinformatics · 2022Review
- Efficient detection and classification of epigenomic changes under multiple conditions.Biometrics · 2022Article
- Fast detection of differential chromatin domains with SCIDDO.Bioinformatics (Oxford, England) · 2021Article
- Integrative Ranking of Enhancer Networks Facilitates the Discovery of Epigenetic Markers in Cancer.Frontiers in genetics · 2021Article
- ICGEC: a comparative method for measuring epigenetic conservation of genes via the integrated signal from multiple histone modifications between cell types.BMC genomics · 2020Article
- LATS kinase-mediated CTCF phosphorylation and selective loss of genomic binding.Science advances · 2020Article
- Integrated transcriptomic and epigenetic data analysis identifiesaberrant expression of genes in acute myeloid leukemia with MLL‑AF9 translocation.Molecular medicine reports · 2020Article
- A comprehensive review of computational prediction of genome-wide features.Briefings in bioinformatics · 2020Article
- Learning common and specific patterns from data of multiple interrelated biological scenarios with matrix factorization.Nucleic acids research · 2019Article
- Genome-wide analysis of epigenetic dynamics across human developmental stages and tissues.BMC genomics · 2019Article
- Methylation-Based Classification of Cervical Squamous Cell Carcinoma into Two New Subclasses Differing in Immune-Related Gene Expression.International journal of molecular sciences · 2018Article
- Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes.Nucleic acids research · 2018Article
- Genome-wide prediction of DNase I hypersensitivity using gene expression.Nature communications · 2017Article
- EpiCompare: an online tool to define and explore genomic regions with tissue or cell type-specific epigenomic features.Bioinformatics (Oxford, England) · 2017Article
- A MAD-Bayes Algorithm for State-Space Inference and Clustering with Application to Querying Large Collections of ChIP-Seq Data Sets.Journal of computational biology : a journal of computational molecular cell biology · 2017Article
- A multidimensional integration analysis reveals potential bridging targets in the process of colorectal cancer liver metastasis.PloS one · 2017Article
- A Hierarchical Framework for State-Space Matrix Inference and Clustering.The annals of applied statistics · 2016Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
Abstract
We propose differential principal component analysis (dPCA) for analyzing multiple ChIP-sequencing datasets to identify differential protein-DNA interactions between two biological conditions. dPCA integrates unsupervised pattern discovery, dimension reduction, and statistical inference into a single framework. It uses a small number of principal components to summarize concisely the major multiprotein synergistic differential patterns between the two conditions. For each pattern, it detects and prioritizes differential genomic loci by comparing the between-condition differences with the within-condition variation among replicate samples. dPCA provides a unique tool for efficiently analyzing large amounts of ChIP-sequencing data to study dynamic changes of gene regulation across different biological conditions. We demonstrate this approach through analyses of differential chromatin patterns at transcription factor binding sites and promoters as well as allele-specific protein-DNA interactions.
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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.