ArticleBMC bioinformatics2017
Correcting nucleotide-specific biases in high-throughput sequencing data.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 26 citations in OpenAlex.
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- ChromBPNet: bias factorized, base-resolution deep learning models of chromatin accessibility reveal cis-regulatory sequence syntax, transcription factor footprints and regulatory variants.bioRxiv : the preprint server for biology · 2025Article
- Metadata-guided feature disentanglement for functional genomics.Bioinformatics (Oxford, England) · 2024Article
- Diversity and Functionality of Bacteria Associated with Different Tissues of Spider Heteropoda venatoria Revealed through Integration of High-Throughput Sequencing and Culturomics Approaches.Microbial ecology · 2024Article
- Correction of transposase sequence bias in ATAC-seq data with rule ensemble modeling.NAR genomics and bioinformatics · 2023Article
- Boquila: NGS read simulator to eliminate read nucleotide bias in sequence analysis.Turkish journal of biology = Turk biyoloji dergisi · 2023Article
- Bibliometric review of ATAC-Seq and its application in gene expression.Briefings in bioinformatics · 2022Review
- Annotating the Insect Regulatory Genome.Insects · 2021Review
- ATAC-Seq Identifies Chromatin Landscapes Linked to the Regulation of Oxidative Stress in the Human Fungal PathogenJournal of fungi (Basel, Switzerland) · 2020Article
- ATAC-seq normalization method can significantly affect differential accessibility analysis and interpretation.Epigenetics & chromatin · 2020Article
- HMMRATAC: a Hidden Markov ModeleR for ATAC-seq.Nucleic acids research · 2019Article
- Use of the nuclear walk-on methodology to determine sites of RNA polymerase II initiation and pausing and quantify nascent RNAs in cells.Methods (San Diego, Calif.) · 2019Review
- Identification of transcription factor binding sites using ATAC-seq.Genome biology · 2019Article
- On the problem of confounders in modeling gene expression.Bioinformatics (Oxford, England) · 2019Review
- BiFET: sequencing Bias-free transcription factor Footprint Enrichment Test.Nucleic acids research · 2019Article
- Genome-wide analysis of chromatin accessibility using ATAC-seq.Methods in cell biology · 2019Review
- Calling Variants in the Clinic: Informed Variant Calling Decisions Based on Biological, Clinical, and Laboratory Variables.Computational and structural biotechnology journal · 2019Review
- NanoPARE: parallel analysis of RNA 5' ends from low-input RNA.Genome research · 2018Article
- Characterization of H5N1 Influenza Virus Quasispecies with Adaptive Hemagglutinin Mutations from Single-Virus Infections of Human Airway Cells.Journal of virology · 2018Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundHigh-throughput sequence (HTS) data exhibit position-specific nucleotide biases that obscure the intended signal and reduce the effectiveness of these data for downstream analyses. These biases are particularly evident in HTS assays for identifying regulatory regions in DNA (DNase-seq, ChIP-seq, FAIRE-seq, ATAC-seq). Biases may result from many experiment-specific factors, including selectivity of DNA restriction enzymes and fragmentation method, as well as sequencing technology-specific factors, such as choice of adapters/primers and sample amplification methods.
resultsWe present a novel method to detect and correct position-specific nucleotide biases in HTS short read data. Our method calculates read-specific weights based on aligned reads to correct the over- or underrepresentation of position-specific nucleotide subsequences, both within and adjacent to the aligned read, relative to a baseline calculated in assay-specific enriched regions. Using HTS data from a variety of ChIP-seq, DNase-seq, FAIRE-seq, and ATAC-seq experiments, we show that our weight-adjusted reads reduce the position-specific nucleotide imbalance across reads and improve the utility of these data for downstream analyses, including identification and characterization of open chromatin peaks and transcription-factor binding sites.
conclusionsA general-purpose method to characterize and correct position-specific nucleotide sequence biases fills the need to recognize and deal with, in a systematic manner, binding-site preference for the growing number of HTS-based epigenetic assays. As the breadth and impact of these biases are better understood, the availability of a standard toolkit to correct them will be important.
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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.