A flexible ChIP-sequencing simulation toolkit
Abstract Background A major challenge in evaluating quantitative ChIP-seq analyses, such as peak calling and differential binding, is a lack of reliable ground truth data. Accurate simulation of ChIP-seq data can mitigate this challenge, but existing...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
BioMed Central
2021
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| Online Access: | https://hdl.handle.net/1721.1/136788 |
| _version_ | 1826207770374832128 |
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| author | Zheng, An Lamkin, Michael Qiu, Yutong Ren, Kevin Goren, Alon Gymrek, Melissa |
| author2 | Massachusetts Institute of Technology. Department of Mathematics |
| author_facet | Massachusetts Institute of Technology. Department of Mathematics Zheng, An Lamkin, Michael Qiu, Yutong Ren, Kevin Goren, Alon Gymrek, Melissa |
| author_sort | Zheng, An |
| collection | MIT |
| description | Abstract
Background
A major challenge in evaluating quantitative ChIP-seq analyses, such as peak calling and differential binding, is a lack of reliable ground truth data. Accurate simulation of ChIP-seq data can mitigate this challenge, but existing frameworks are either too cumbersome to apply genome-wide or unable to model a number of important experimental conditions in ChIP-seq.
Results
We present ChIPs, a toolkit for rapidly simulating ChIP-seq data using statistical models of key experimental steps. We demonstrate how ChIPs can be used for a range of applications, including benchmarking analysis tools and evaluating the impact of various experimental parameters. ChIPs is implemented as a standalone command-line program written in C++ and is available from
https://github.com/gymreklab/chips
.
Conclusions
ChIPs is an efficient ChIP-seq simulation framework that generates realistic datasets over a flexible range of experimental conditions. It can serve as an important component in various ChIP-seq analyses where ground truth data are needed. |
| first_indexed | 2024-09-23T13:54:41Z |
| format | Article |
| id | mit-1721.1/136788 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T13:54:41Z |
| publishDate | 2021 |
| publisher | BioMed Central |
| record_format | dspace |
| spelling | mit-1721.1/1367882023-02-23T16:55:27Z A flexible ChIP-sequencing simulation toolkit Zheng, An Lamkin, Michael Qiu, Yutong Ren, Kevin Goren, Alon Gymrek, Melissa Massachusetts Institute of Technology. Department of Mathematics Abstract Background A major challenge in evaluating quantitative ChIP-seq analyses, such as peak calling and differential binding, is a lack of reliable ground truth data. Accurate simulation of ChIP-seq data can mitigate this challenge, but existing frameworks are either too cumbersome to apply genome-wide or unable to model a number of important experimental conditions in ChIP-seq. Results We present ChIPs, a toolkit for rapidly simulating ChIP-seq data using statistical models of key experimental steps. We demonstrate how ChIPs can be used for a range of applications, including benchmarking analysis tools and evaluating the impact of various experimental parameters. ChIPs is implemented as a standalone command-line program written in C++ and is available from https://github.com/gymreklab/chips . Conclusions ChIPs is an efficient ChIP-seq simulation framework that generates realistic datasets over a flexible range of experimental conditions. It can serve as an important component in various ChIP-seq analyses where ground truth data are needed. 2021-11-01T14:33:23Z 2021-11-01T14:33:23Z 2021-04-20 2021-04-25T04:50:01Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/136788 BMC Bioinformatics. 2021 Apr 20;22(1):201 PUBLISHER_CC en https://doi.org/10.1186/s12859-021-04097-5 Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf BioMed Central BioMed Central |
| spellingShingle | Zheng, An Lamkin, Michael Qiu, Yutong Ren, Kevin Goren, Alon Gymrek, Melissa A flexible ChIP-sequencing simulation toolkit |
| title | A flexible ChIP-sequencing simulation toolkit |
| title_full | A flexible ChIP-sequencing simulation toolkit |
| title_fullStr | A flexible ChIP-sequencing simulation toolkit |
| title_full_unstemmed | A flexible ChIP-sequencing simulation toolkit |
| title_short | A flexible ChIP-sequencing simulation toolkit |
| title_sort | flexible chip sequencing simulation toolkit |
| url | https://hdl.handle.net/1721.1/136788 |
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