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Article: Impact of sequencing depth and read length on single cell RNA sequencing data of T cells
Title | Impact of sequencing depth and read length on single cell RNA sequencing data of T cells |
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Authors | |
Issue Date | 2017 |
Citation | Scientific Reports, 2017, v. 7, n. 1, article no. 12781 (2017) How to Cite? |
Abstract | © 2017 The Author(s). Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81%-100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells. |
Persistent Identifier | http://hdl.handle.net/10722/262769 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Rizzetto, Simone | - |
dc.contributor.author | Eltahla, Auda A. | - |
dc.contributor.author | Lin, Peijie | - |
dc.contributor.author | Bull, Rowena | - |
dc.contributor.author | Lloyd, Andrew R. | - |
dc.contributor.author | Ho, Joshua W.K. | - |
dc.contributor.author | Venturi, Vanessa | - |
dc.contributor.author | Luciani, Fabio | - |
dc.date.accessioned | 2018-10-08T02:46:59Z | - |
dc.date.available | 2018-10-08T02:46:59Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Scientific Reports, 2017, v. 7, n. 1, article no. 12781 (2017) | - |
dc.identifier.uri | http://hdl.handle.net/10722/262769 | - |
dc.description.abstract | © 2017 The Author(s). Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81%-100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells. | - |
dc.language | eng | - |
dc.relation.ispartof | Scientific Reports | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.title | Impact of sequencing depth and read length on single cell RNA sequencing data of T cells | - |
dc.type | Article | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1038/s41598-017-12989-x | - |
dc.identifier.scopus | eid_2-s2.0-85030768269 | - |
dc.identifier.volume | 7 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | article no. 12781 (2017) | - |
dc.identifier.epage | article no. 12781 (2017) | - |
dc.identifier.eissn | 2045-2322 | - |
dc.identifier.isi | WOS:000412492400007 | - |
dc.identifier.issnl | 2045-2322 | - |