Cargando…
scReadSim: a single-cell RNA-seq and ATAC-seq read simulator
Benchmarking single-cell RNA-seq (scRNA-seq) and single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) computational tools demands simulators to generate realistic sequencing reads. However, none of the few read simulators aim to mimic real data. To fill this gap, we i...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657386/ https://www.ncbi.nlm.nih.gov/pubmed/37980428 http://dx.doi.org/10.1038/s41467-023-43162-w |
_version_ | 1785148140331991040 |
---|---|
author | Yan, Guanao Song, Dongyuan Li, Jingyi Jessica |
author_facet | Yan, Guanao Song, Dongyuan Li, Jingyi Jessica |
author_sort | Yan, Guanao |
collection | PubMed |
description | Benchmarking single-cell RNA-seq (scRNA-seq) and single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) computational tools demands simulators to generate realistic sequencing reads. However, none of the few read simulators aim to mimic real data. To fill this gap, we introduce scReadSim, a single-cell RNA-seq and ATAC-seq read simulator that allows user-specified ground truths and generates synthetic sequencing reads (in a FASTQ or BAM file) by mimicking real data. At both read-sequence and read-count levels, scReadSim mimics real scRNA-seq and scATAC-seq data. Moreover, scReadSim provides ground truths, including unique molecular identifier (UMI) counts for scRNA-seq and open chromatin regions for scATAC-seq. In particular, scReadSim allows users to design cell-type-specific ground-truth open chromatin regions for scATAC-seq data generation. In benchmark applications of scReadSim, we show that UMI-tools achieves the top accuracy in scRNA-seq UMI deduplication, and HMMRATAC and MACS3 achieve the top performance in scATAC-seq peak calling. |
format | Online Article Text |
id | pubmed-10657386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106573862023-11-18 scReadSim: a single-cell RNA-seq and ATAC-seq read simulator Yan, Guanao Song, Dongyuan Li, Jingyi Jessica Nat Commun Article Benchmarking single-cell RNA-seq (scRNA-seq) and single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) computational tools demands simulators to generate realistic sequencing reads. However, none of the few read simulators aim to mimic real data. To fill this gap, we introduce scReadSim, a single-cell RNA-seq and ATAC-seq read simulator that allows user-specified ground truths and generates synthetic sequencing reads (in a FASTQ or BAM file) by mimicking real data. At both read-sequence and read-count levels, scReadSim mimics real scRNA-seq and scATAC-seq data. Moreover, scReadSim provides ground truths, including unique molecular identifier (UMI) counts for scRNA-seq and open chromatin regions for scATAC-seq. In particular, scReadSim allows users to design cell-type-specific ground-truth open chromatin regions for scATAC-seq data generation. In benchmark applications of scReadSim, we show that UMI-tools achieves the top accuracy in scRNA-seq UMI deduplication, and HMMRATAC and MACS3 achieve the top performance in scATAC-seq peak calling. Nature Publishing Group UK 2023-11-18 /pmc/articles/PMC10657386/ /pubmed/37980428 http://dx.doi.org/10.1038/s41467-023-43162-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Yan, Guanao Song, Dongyuan Li, Jingyi Jessica scReadSim: a single-cell RNA-seq and ATAC-seq read simulator |
title | scReadSim: a single-cell RNA-seq and ATAC-seq read simulator |
title_full | scReadSim: a single-cell RNA-seq and ATAC-seq read simulator |
title_fullStr | scReadSim: a single-cell RNA-seq and ATAC-seq read simulator |
title_full_unstemmed | scReadSim: a single-cell RNA-seq and ATAC-seq read simulator |
title_short | scReadSim: a single-cell RNA-seq and ATAC-seq read simulator |
title_sort | screadsim: a single-cell rna-seq and atac-seq read simulator |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657386/ https://www.ncbi.nlm.nih.gov/pubmed/37980428 http://dx.doi.org/10.1038/s41467-023-43162-w |
work_keys_str_mv | AT yanguanao screadsimasinglecellrnaseqandatacseqreadsimulator AT songdongyuan screadsimasinglecellrnaseqandatacseqreadsimulator AT lijingyijessica screadsimasinglecellrnaseqandatacseqreadsimulator |