CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data

Abstract We develop CellSIUS (Cell Subtype Identification from Upregulated gene Sets) to fill a methodology gap for rare cell population identification for scRNA-seq data. CellSIUS outperforms existing algorithms for specificity and selectivity for rare cell types and their transcriptomic signature...
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Autor*in:	Rebekka Wegmann [verfasserIn] Marilisa Neri [verfasserIn] Sven Schuierer [verfasserIn] Bilada Bilican [verfasserIn] Huyen Hartkopf [verfasserIn] Florian Nigsch [verfasserIn] Felipa Mapa [verfasserIn] Annick Waldt [verfasserIn] Rachel Cuttat [verfasserIn] Max R. Salick [verfasserIn] Joe Raymond [verfasserIn] Ajamete Kaykas [verfasserIn] Guglielmo Roma [verfasserIn] Caroline Gubser Keller [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Single-cell RNA sequencing Data analysis Rare cell types Clustering Software Benchmarking

Übergeordnetes Werk:	In: Genome Biology - BMC, 2014, 20(2019), 1, Seite 21
Übergeordnetes Werk:	volume:20 ; year:2019 ; number:1 ; pages:21

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1186/s13059-019-1739-7

Katalog-ID:	DOAJ056132115

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520			\|a Abstract We develop CellSIUS (Cell Subtype Identification from Upregulated gene Sets) to fill a methodology gap for rare cell population identification for scRNA-seq data. CellSIUS outperforms existing algorithms for specificity and selectivity for rare cell types and their transcriptomic signature identification in synthetic and complex biological data. Characterization of a human pluripotent cell differentiation protocol recapitulating deep-layer corticogenesis using CellSIUS reveals unrecognized complexity in human stem cell-derived cellular populations. CellSIUS enables identification of novel rare cell populations and their signature genes providing the means to study those populations in vitro in light of their role in health and disease.
650		4	\|a Single-cell RNA sequencing
650		4	\|a Data analysis
650		4	\|a Rare cell types
650		4	\|a Clustering
650		4	\|a Software
650		4	\|a Benchmarking
653		0	\|a Biology (General)
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allfieldsSound	10.1186/s13059-019-1739-7 doi (DE-627)DOAJ056132115 (DE-599)DOAJ39c1e83d8d7d43228770031c5358d8f1 DE-627 ger DE-627 rakwb eng QH301-705.5 QH426-470 Rebekka Wegmann verfasserin aut CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract We develop CellSIUS (Cell Subtype Identification from Upregulated gene Sets) to fill a methodology gap for rare cell population identification for scRNA-seq data. CellSIUS outperforms existing algorithms for specificity and selectivity for rare cell types and their transcriptomic signature identification in synthetic and complex biological data. Characterization of a human pluripotent cell differentiation protocol recapitulating deep-layer corticogenesis using CellSIUS reveals unrecognized complexity in human stem cell-derived cellular populations. CellSIUS enables identification of novel rare cell populations and their signature genes providing the means to study those populations in vitro in light of their role in health and disease. Single-cell RNA sequencing Data analysis Rare cell types Clustering Software Benchmarking Biology (General) Genetics Marilisa Neri verfasserin aut Sven Schuierer verfasserin aut Bilada Bilican verfasserin aut Huyen Hartkopf verfasserin aut Florian Nigsch verfasserin aut Felipa Mapa verfasserin aut Annick Waldt verfasserin aut Rachel Cuttat verfasserin aut Max R. Salick verfasserin aut Joe Raymond verfasserin aut Ajamete Kaykas verfasserin aut Guglielmo Roma verfasserin aut Caroline Gubser Keller verfasserin aut In Genome Biology BMC, 2014 20(2019), 1, Seite 21 (DE-627)326173617 (DE-600)2040529-7 1474760X nnns volume:20 year:2019 number:1 pages:21 https://doi.org/10.1186/s13059-019-1739-7 kostenfrei https://doaj.org/article/39c1e83d8d7d43228770031c5358d8f1 kostenfrei http://link.springer.com/article/10.1186/s13059-019-1739-7 kostenfrei https://doaj.org/toc/1474-760X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2019 1 21
language	English
source	In Genome Biology 20(2019), 1, Seite 21 volume:20 year:2019 number:1 pages:21
sourceStr	In Genome Biology 20(2019), 1, Seite 21 volume:20 year:2019 number:1 pages:21
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topic_facet	Single-cell RNA sequencing Data analysis Rare cell types Clustering Software Benchmarking Biology (General) Genetics
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authorswithroles_txt_mv	Rebekka Wegmann @@aut@@ Marilisa Neri @@aut@@ Sven Schuierer @@aut@@ Bilada Bilican @@aut@@ Huyen Hartkopf @@aut@@ Florian Nigsch @@aut@@ Felipa Mapa @@aut@@ Annick Waldt @@aut@@ Rachel Cuttat @@aut@@ Max R. Salick @@aut@@ Joe Raymond @@aut@@ Ajamete Kaykas @@aut@@ Guglielmo Roma @@aut@@ Caroline Gubser Keller @@aut@@
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callnumber-first	Q - Science
author	Rebekka Wegmann
spellingShingle	Rebekka Wegmann misc QH301-705.5 misc QH426-470 misc Single-cell RNA sequencing misc Data analysis misc Rare cell types misc Clustering misc Software misc Benchmarking misc Biology (General) misc Genetics CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data
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topic_title	QH301-705.5 QH426-470 CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data Single-cell RNA sequencing Data analysis Rare cell types Clustering Software Benchmarking
topic	misc QH301-705.5 misc QH426-470 misc Single-cell RNA sequencing misc Data analysis misc Rare cell types misc Clustering misc Software misc Benchmarking misc Biology (General) misc Genetics
topic_unstemmed	misc QH301-705.5 misc QH426-470 misc Single-cell RNA sequencing misc Data analysis misc Rare cell types misc Clustering misc Software misc Benchmarking misc Biology (General) misc Genetics
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title	CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data
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title_full	CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data
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title_sort	cellsius provides sensitive and specific detection of rare cell populations from complex single-cell rna-seq data
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title_auth	CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data
abstract	Abstract We develop CellSIUS (Cell Subtype Identification from Upregulated gene Sets) to fill a methodology gap for rare cell population identification for scRNA-seq data. CellSIUS outperforms existing algorithms for specificity and selectivity for rare cell types and their transcriptomic signature identification in synthetic and complex biological data. Characterization of a human pluripotent cell differentiation protocol recapitulating deep-layer corticogenesis using CellSIUS reveals unrecognized complexity in human stem cell-derived cellular populations. CellSIUS enables identification of novel rare cell populations and their signature genes providing the means to study those populations in vitro in light of their role in health and disease.
abstractGer	Abstract We develop CellSIUS (Cell Subtype Identification from Upregulated gene Sets) to fill a methodology gap for rare cell population identification for scRNA-seq data. CellSIUS outperforms existing algorithms for specificity and selectivity for rare cell types and their transcriptomic signature identification in synthetic and complex biological data. Characterization of a human pluripotent cell differentiation protocol recapitulating deep-layer corticogenesis using CellSIUS reveals unrecognized complexity in human stem cell-derived cellular populations. CellSIUS enables identification of novel rare cell populations and their signature genes providing the means to study those populations in vitro in light of their role in health and disease.
abstract_unstemmed	Abstract We develop CellSIUS (Cell Subtype Identification from Upregulated gene Sets) to fill a methodology gap for rare cell population identification for scRNA-seq data. CellSIUS outperforms existing algorithms for specificity and selectivity for rare cell types and their transcriptomic signature identification in synthetic and complex biological data. Characterization of a human pluripotent cell differentiation protocol recapitulating deep-layer corticogenesis using CellSIUS reveals unrecognized complexity in human stem cell-derived cellular populations. CellSIUS enables identification of novel rare cell populations and their signature genes providing the means to study those populations in vitro in light of their role in health and disease.
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title_short	CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data
url	https://doi.org/10.1186/s13059-019-1739-7 https://doaj.org/article/39c1e83d8d7d43228770031c5358d8f1 http://link.springer.com/article/10.1186/s13059-019-1739-7 https://doaj.org/toc/1474-760X
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up_date	2024-07-03T19:03:20.599Z
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CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data

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