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GeneSwitches: ordering gene expression and functional events in single-cell experiments

GeneSwitches: ordering gene expression and functional events in single-cell experiments
GeneSwitches: ordering gene expression and functional events in single-cell experiments

SUMMARY: Emerging single-cell RNA-sequencing data technologies has made it possible to capture and assess the gene expression of individual cells. Based on the similarity of gene expression profiles, many tools have been developed to generate an in silico ordering of cells in the form of pseudo-time trajectories. However, these tools do not provide a means to find the ordering of critical gene expression changes over pseudo-time. We present GeneSwitches, a tool that takes any single-cell pseudo-time trajectory and determines the precise order of gene expression and functional-event changes over time. GeneSwitches uses a statistical framework based on logistic regression to identify the order in which genes are either switched on or off along pseudo-time. With this information, users can identify the order in which surface markers appear, investigate how functional ontologies are gained or lost over time and compare the ordering of switching genes from two related pseudo-temporal processes.

AVAILABILITY: GeneSwitches is available at https://geneswitches.ddnetbio.com.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Gene Expression Profiling, RNA, Sequence Analysis, RNA, Single-Cell Analysis, Software
1367-4803
3273-3275
Cao, Elaine Y
f1c98fe8-3ab7-402f-97b9-1e8d23d6ff5c
Ouyang, John F
ce6f93a5-b40f-4add-8d7b-3ae795c1a4cb
Rackham, Owen J L
8122eb1f-6e9f-4da5-90e1-ce108ccbbcbf
Cao, Elaine Y
f1c98fe8-3ab7-402f-97b9-1e8d23d6ff5c
Ouyang, John F
ce6f93a5-b40f-4add-8d7b-3ae795c1a4cb
Rackham, Owen J L
8122eb1f-6e9f-4da5-90e1-ce108ccbbcbf

Cao, Elaine Y, Ouyang, John F and Rackham, Owen J L (2020) GeneSwitches: ordering gene expression and functional events in single-cell experiments. Bioinformatics, 36 (10), 3273-3275. (doi:10.1093/bioinformatics/btaa099).

Record type: Article

Abstract

SUMMARY: Emerging single-cell RNA-sequencing data technologies has made it possible to capture and assess the gene expression of individual cells. Based on the similarity of gene expression profiles, many tools have been developed to generate an in silico ordering of cells in the form of pseudo-time trajectories. However, these tools do not provide a means to find the ordering of critical gene expression changes over pseudo-time. We present GeneSwitches, a tool that takes any single-cell pseudo-time trajectory and determines the precise order of gene expression and functional-event changes over time. GeneSwitches uses a statistical framework based on logistic regression to identify the order in which genes are either switched on or off along pseudo-time. With this information, users can identify the order in which surface markers appear, investigate how functional ontologies are gained or lost over time and compare the ordering of switching genes from two related pseudo-temporal processes.

AVAILABILITY: GeneSwitches is available at https://geneswitches.ddnetbio.com.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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More information

Accepted/In Press date: 10 February 2020
e-pub ahead of print date: 14 February 2020
Published date: 15 May 2020
Additional Information: © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Keywords: Gene Expression Profiling, RNA, Sequence Analysis, RNA, Single-Cell Analysis, Software

Identifiers

Local EPrints ID: 447925
URI: http://eprints.soton.ac.uk/id/eprint/447925
ISSN: 1367-4803
PURE UUID: 40b5e2db-ee2d-4e69-b204-38423ae56732
ORCID for Owen J L Rackham: ORCID iD orcid.org/0000-0002-4390-0872

Catalogue record

Date deposited: 26 Mar 2021 17:30
Last modified: 28 Apr 2022 02:30

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Contributors

Author: Elaine Y Cao
Author: John F Ouyang

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