Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis.

As newer single-cell protocols generate increasingly more cells at reduced sequencing depths, the value of a higher read depth may be overlooked. Using data from three different single-cell RNA-seq protocols that lend themselves to having either higher read depth (Smart-seq) or many cells (MARS-seq...

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Autores principales:	Morten Seirup, Li-Fang Chu, Srikumar Sengupta, Ning Leng, Hadley Browder, Kevin Kapadia, Christina M Shafer, Bret Duffin, Angela L Elwell, Jennifer M Bolin, Scott Swanson, Ron Stewart, Christina Kendziorski, James A Thomson, Rhonda Bacher
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/653545f9595e443993e4a86848c2c3b4
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id	oai:doaj.org-article:653545f9595e443993e4a86848c2c3b4
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spelling	oai:doaj.org-article:653545f9595e443993e4a86848c2c3b42021-12-02T20:05:46ZReproducibility across single-cell RNA-seq protocols for spatial ordering analysis.1932-620310.1371/journal.pone.0239711https://doaj.org/article/653545f9595e443993e4a86848c2c3b42020-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0239711https://doaj.org/toc/1932-6203As newer single-cell protocols generate increasingly more cells at reduced sequencing depths, the value of a higher read depth may be overlooked. Using data from three different single-cell RNA-seq protocols that lend themselves to having either higher read depth (Smart-seq) or many cells (MARS-seq and 10X), we evaluate their ability to recapitulate biological signals in the context of spatial reconstruction. Overall, we find gene expression profiles after spatial reconstruction analysis are highly reproducible between datasets despite being generated by different protocols and using different computational algorithms. While UMI-based protocols such as 10X and MARS-seq allow for capturing more cells, Smart-seq's higher sensitivity and read-depth allow for analysis of lower expressed genes and isoforms. Additionally, we evaluate trade-offs for each protocol by performing subsampling analyses and find that optimizing the balance between sequencing depth and number of cells within a protocol is necessary for efficient use of resources. Our analysis emphasizes the importance of selecting a protocol based on the biological questions and features of interest.Morten SeirupLi-Fang ChuSrikumar SenguptaNing LengHadley BrowderKevin KapadiaChristina M ShaferBret DuffinAngela L ElwellJennifer M BolinScott SwansonRon StewartChristina KendziorskiJames A ThomsonRhonda BacherPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 15, Iss 9, p e0239711 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Morten Seirup Li-Fang Chu Srikumar Sengupta Ning Leng Hadley Browder Kevin Kapadia Christina M Shafer Bret Duffin Angela L Elwell Jennifer M Bolin Scott Swanson Ron Stewart Christina Kendziorski James A Thomson Rhonda Bacher Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis.
description	As newer single-cell protocols generate increasingly more cells at reduced sequencing depths, the value of a higher read depth may be overlooked. Using data from three different single-cell RNA-seq protocols that lend themselves to having either higher read depth (Smart-seq) or many cells (MARS-seq and 10X), we evaluate their ability to recapitulate biological signals in the context of spatial reconstruction. Overall, we find gene expression profiles after spatial reconstruction analysis are highly reproducible between datasets despite being generated by different protocols and using different computational algorithms. While UMI-based protocols such as 10X and MARS-seq allow for capturing more cells, Smart-seq's higher sensitivity and read-depth allow for analysis of lower expressed genes and isoforms. Additionally, we evaluate trade-offs for each protocol by performing subsampling analyses and find that optimizing the balance between sequencing depth and number of cells within a protocol is necessary for efficient use of resources. Our analysis emphasizes the importance of selecting a protocol based on the biological questions and features of interest.
format	article
author	Morten Seirup Li-Fang Chu Srikumar Sengupta Ning Leng Hadley Browder Kevin Kapadia Christina M Shafer Bret Duffin Angela L Elwell Jennifer M Bolin Scott Swanson Ron Stewart Christina Kendziorski James A Thomson Rhonda Bacher
author_facet	Morten Seirup Li-Fang Chu Srikumar Sengupta Ning Leng Hadley Browder Kevin Kapadia Christina M Shafer Bret Duffin Angela L Elwell Jennifer M Bolin Scott Swanson Ron Stewart Christina Kendziorski James A Thomson Rhonda Bacher
author_sort	Morten Seirup
title	Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis.
title_short	Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis.
title_full	Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis.
title_fullStr	Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis.
title_full_unstemmed	Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis.
title_sort	reproducibility across single-cell rna-seq protocols for spatial ordering analysis.
publisher	Public Library of Science (PLoS)
publishDate	2020
url	https://doaj.org/article/653545f9595e443993e4a86848c2c3b4
work_keys_str_mv	AT mortenseirup reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT lifangchu reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT srikumarsengupta reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT ningleng reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT hadleybrowder reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT kevinkapadia reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT christinamshafer reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT bretduffin reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT angelalelwell reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT jennifermbolin reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT scottswanson reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT ronstewart reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT christinakendziorski reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT jamesathomson reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis AT rhondabacher reproducibilityacrosssinglecellrnaseqprotocolsforspatialorderinganalysis
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Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis.

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