BackgroundEpigenomic profiling assays such as ChIP-seq have been widely used to map the genome-wide enrichment profiles of chromatin-associated proteins and posttranslational histone modifications. Sequencing depth is a key parameter in experimental design and quality control. However, due to variable sequencing depth requirements across experimental conditions, it can be challenging to determine optimal sequencing depth, particularly for projects involving multiple targets or cell types.ResultsWe developed the peaksat R package to provide target read depth estimates for epigenomic experiments based on the analysis of peak saturation curves. We applied peaksat to establish the distinctive read depth requirements for ChIP-seq studies of histone modifications in different cell lines. Using peaksat, we were able to estimate the target read depth required per library to obtain high-quality peak calls for downstream analysis. In addition, peaksat was applied to other sequence-enrichment methods including CUT&RUN and ATAC-seq.Conclusionpeaksat addresses a need for researchers to make informed decisions about whether their sequencing data has been generated to an adequate depth and subsequently sufficient meaningful peaks, and failing that, how many more reads would be required per library. peaksat is applicable to other sequence-based methods that include calling peaks in their analysis.
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Univ Chicago, Dept Human Genet, CLSC, Chicago, IL 60637 USAUniv Chicago, Dept Human Genet, CLSC, Chicago, IL 60637 USA
He, Xin
Cicek, A. Ercument
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Carnegie Mellon Univ, Computat Biol Dept, Pittsburgh, PA 15213 USA
Bilkent Univ, Dept Comp Engn, TR-06800 Ankara, TurkeyUniv Chicago, Dept Human Genet, CLSC, Chicago, IL 60637 USA
Cicek, A. Ercument
Wang, Yuhao
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MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02139 USAUniv Chicago, Dept Human Genet, CLSC, Chicago, IL 60637 USA
Wang, Yuhao
Schulz, Marcel H.
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Univ Saarland, Multimodal Comp & Interact, D-66123 Saarbrucken, Saarland, Germany
Max Planck Inst Informat, D-66123 Saarbrucken, Saarland, GermanyUniv Chicago, Dept Human Genet, CLSC, Chicago, IL 60637 USA
Schulz, Marcel H.
Le, Hai-Son
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Carnegie Mellon Univ, Computat Biol Dept, Pittsburgh, PA 15213 USAUniv Chicago, Dept Human Genet, CLSC, Chicago, IL 60637 USA
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College of Biological Engineering, Henan University of Technology, Zhengzhou, Henan, ChinaCollege of Biological Engineering, Henan University of Technology, Zhengzhou, Henan, China
Zhang, Li
Hu, Yuansen
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College of Biological Engineering, Henan University of Technology, Zhengzhou, Henan, ChinaCollege of Biological Engineering, Henan University of Technology, Zhengzhou, Henan, China
Hu, Yuansen
Wang, Jinshui
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College of Biological Engineering, Henan University of Technology, Zhengzhou, Henan, ChinaCollege of Biological Engineering, Henan University of Technology, Zhengzhou, Henan, China
Wang, Jinshui
Zhang, Guangle
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College of Biological Engineering, Henan University of Technology, Zhengzhou, Henan, ChinaCollege of Biological Engineering, Henan University of Technology, Zhengzhou, Henan, China
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Macquarie Univ, Dept Stat, N Ryde, NSW 2109, Australia
CSIRO Math & Informat Sci, N Ryde, NSW 2113, Australia
Wellcome Trust Ctr Human Genet, Oxford OX3 7BN, EnglandMacquarie Univ, Dept Stat, N Ryde, NSW 2109, Australia
Humburg, Peter
Helliwell, Chris A.
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CSIRO Plant Ind, Canberra, ACT 2601, AustraliaMacquarie Univ, Dept Stat, N Ryde, NSW 2109, Australia
Helliwell, Chris A.
Bulger, David
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Macquarie Univ, Dept Stat, N Ryde, NSW 2109, AustraliaMacquarie Univ, Dept Stat, N Ryde, NSW 2109, Australia
Bulger, David
Stone, Glenn
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CSIRO Math & Informat Sci, N Ryde, NSW 2113, AustraliaMacquarie Univ, Dept Stat, N Ryde, NSW 2109, Australia
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Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute/Harvard School of Public HealthDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute/Harvard School of Public Health
Hyunjin Shin
Tao Liu
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Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute/Harvard School of Public HealthDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute/Harvard School of Public Health
Tao Liu
Xikun Duan
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Department of Bioinformatics, School of Life Science and Technology, TongjiDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute/Harvard School of Public Health
Xikun Duan
Yong Zhang
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机构:
Department of Bioinformatics, School of Life Science and Technology, TongjiDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute/Harvard School of Public Health
Yong Zhang
XShirley Liu
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Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute/Harvard School of Public HealthDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute/Harvard School of Public Health
机构:
Gladstone Inst, Bioinformat Core, San Francisco, CA USAGladstone Inst, San Francisco, CA 94158 USA
Thomas, Reuben
Thomas, Sean
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Gladstone Inst, Bioinformat Core, San Francisco, CA USAGladstone Inst, San Francisco, CA 94158 USA
Thomas, Sean
Holloway, Alisha K.
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机构:
Gladstone Inst, San Francisco, CA 94158 USA
Phylos Biosciences, Bioinformat, San Francisco, CA USA
Univ Calif San Francisco, Biostat, San Francisco, CA 94143 USAGladstone Inst, San Francisco, CA 94158 USA
Holloway, Alisha K.
Pollard, Katherine S.
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Gladstone Inst, San Francisco, CA 94158 USA
Univ Calif San Francisco, Biostat, San Francisco, CA 94143 USAGladstone Inst, San Francisco, CA 94158 USA