ArticleBioinformatics (Oxford, England)2022
DiffChIPL: a differential peak analysis method for high-throughput sequencing data with biological replicates based on limma.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
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- The Critical Role of APOE+ Macrophages in the Immune Microenvironment and Prognosis of Lung Adenocarcinoma.Journal of cellular and molecular medicine · 2025Article
- Mitochondrial Pathway Signature (MitoPS) predicts immunotherapy response and reveals NDUFB10 as a key immune regulator in lung adenocarcinoma.Journal for immunotherapy of cancer · 2025Article
- Modular-Based Synergetic Mechanisms of Jasminoidin and Ursodeoxycholic Acid in Cerebral Ischemia Therapy.Biomedicines · 2025Article
- Identification of novel biomarkers associated with immune infiltration in major depression disorder and atopic dermatitis.Archives of dermatological research · 2025Article
- Immune Regulation and ECM-Related Pathway Enrichment Reveal ATP2A3 as a Prognostic Biomarker for Nonspecific Orbital Inflammation: An Integrated Machine Learning and Mendelian Randomization Analysis.Mediators of inflammation · 2025Article
- Single-cell and multi-omics analysis reveals the role of stem cells in prognosis and immunotherapy of lung adenocarcinoma patients.Frontiers in immunology · 2025Article
- Integrated machine learning and Mendelian randomization reveal PALMD as a prognostic biomarker for nonspecific orbital inflammation.Scientific reports · 2024Article
- CBFA2T3-GLIS2 mediates transcriptional regulation of developmental pathways through a gene regulatory network.Nature communications · 2024Article
- MOCHA's advanced statistical modeling of scATAC-seq data enables functional genomic inference in large human cohorts.Nature communications · 2024Article
- Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.Frontiers in cardiovascular medicine · 2024Article
- Establishing a prognostic model based on immune-related genes and identification of BIRC5 as a potential biomarker for lung adenocarcinoma patients.BMC cancer · 2023Article
- Integrating multiple machine learning methods to construct glutamine metabolism-related signatures in lung adenocarcinoma.Frontiers in endocrinology · 2023Article
- A novel signature predicts prognosis and immunotherapy in lung adenocarcinoma based on cancer-associated fibroblasts.Frontiers in immunology · 2023Article
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3 authors.
Funding
Abstract
motivationChIP-seq detects protein-DNA interactions within chromatin, such as that of chromatin structural components and transcription machinery. ChIP-seq profiles are often noisy and variable across replicates, posing a challenge to the development of effective algorithms to accurately detect differential peaks. Methods have recently been designed for this purpose but sometimes yield conflicting results that are inconsistent with the underlying biology. Most existing algorithms perform well on limited datasets. To improve differential analysis of ChIP-seq, we present a novel Differential analysis method for ChIP-seq based on Limma (DiffChIPL).
resultsDiffChIPL is adaptive to asymmetrical or symmetrical data and can accurately report global differences. We used simulated and real datasets for transcription factors (TFs) and histone modification marks to validate and benchmark our algorithm. DiffChIPL shows superior performance in sensitivity and false positive rate in different simulations and control datasets. DiffChIPL also performs well on real ChIP-seq, CUT&RUN, CUT&Tag and ATAC-seq datasets. DiffChIPL is an accurate and robust method, exhibiting better performance in differential analysis for a variety of applications including TF binding, histone modifications and chromatin accessibility. AVAILABILITY AND IMPLEMENTATION: https://github.com/yancychy/DiffChIPL. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.