Prediction of cell position using single-cell transcriptomic data: an iterative procedure

Autores
Alonso, Andrés Mariano; Carrea, Alejandra; Diambra, Luis Anibal
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Single-cell sequencing reveals cellular heterogeneity but not cell localization. However, by combining single-cell transcriptomic data with a reference atlas of a small set of genes, it would be possible to predict the position of individual cells and reconstruct the spatial expression profile of thousands of genes reported in the single-cell study. To develop new algorithms for this purpose, the Dialogue for Reverse Engineering Assessments and Methods (DREAM) consortium organized a crowd-sourced competition known as DREAM Single Cell Transcriptomics Challenge (SCTC). In the spirit of this framework, we describe here the proposed procedures for adequate reference genes selection, and an iterative procedure to predict spatial expression profile of other genes.
Fil: Alonso, Andrés Mariano. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús). Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús); Argentina
Fil: Carrea, Alejandra. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Diambra, Luis Anibal. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Materia
SINGLE-CELL SEQUENCING
RNASEQ
GENE EXPRESSION PATTERNS
PATTERNS RECONSTRUCTION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/129011
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Prediction of cell position using single-cell transcriptomic data: an iterative procedureAlonso, Andrés MarianoCarrea, AlejandraDiambra, Luis AnibalSINGLE-CELL SEQUENCINGRNASEQGENE EXPRESSION PATTERNSPATTERNS RECONSTRUCTIONhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Single-cell sequencing reveals cellular heterogeneity but not cell localization. However, by combining single-cell transcriptomic data with a reference atlas of a small set of genes, it would be possible to predict the position of individual cells and reconstruct the spatial expression profile of thousands of genes reported in the single-cell study. To develop new algorithms for this purpose, the Dialogue for Reverse Engineering Assessments and Methods (DREAM) consortium organized a crowd-sourced competition known as DREAM Single Cell Transcriptomics Challenge (SCTC). In the spirit of this framework, we describe here the proposed procedures for adequate reference genes selection, and an iterative procedure to predict spatial expression profile of other genes.Fil: Alonso, Andrés Mariano. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús). Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús); ArgentinaFil: Carrea, Alejandra. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Diambra, Luis Anibal. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaF1000 Research Ltd2019-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/129011Alonso, Andrés Mariano; Carrea, Alejandra; Diambra, Luis Anibal; Prediction of cell position using single-cell transcriptomic data: an iterative procedure; F1000 Research Ltd; F1000Research; 8; 1775; 10-2019; 1-72046-1402CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.12688/f1000research.20715.1info:eu-repo/semantics/altIdentifier/url/https://f1000research.com/articles/8-1775/v1info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:08:42Zoai:ri.conicet.gov.ar:11336/129011instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:08:43.168CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Prediction of cell position using single-cell transcriptomic data: an iterative procedure
title Prediction of cell position using single-cell transcriptomic data: an iterative procedure
spellingShingle Prediction of cell position using single-cell transcriptomic data: an iterative procedure
Alonso, Andrés Mariano
SINGLE-CELL SEQUENCING
RNASEQ
GENE EXPRESSION PATTERNS
PATTERNS RECONSTRUCTION
title_short Prediction of cell position using single-cell transcriptomic data: an iterative procedure
title_full Prediction of cell position using single-cell transcriptomic data: an iterative procedure
title_fullStr Prediction of cell position using single-cell transcriptomic data: an iterative procedure
title_full_unstemmed Prediction of cell position using single-cell transcriptomic data: an iterative procedure
title_sort Prediction of cell position using single-cell transcriptomic data: an iterative procedure
dc.creator.none.fl_str_mv Alonso, Andrés Mariano
Carrea, Alejandra
Diambra, Luis Anibal
author Alonso, Andrés Mariano
author_facet Alonso, Andrés Mariano
Carrea, Alejandra
Diambra, Luis Anibal
author_role author
author2 Carrea, Alejandra
Diambra, Luis Anibal
author2_role author
author
dc.subject.none.fl_str_mv SINGLE-CELL SEQUENCING
RNASEQ
GENE EXPRESSION PATTERNS
PATTERNS RECONSTRUCTION
topic SINGLE-CELL SEQUENCING
RNASEQ
GENE EXPRESSION PATTERNS
PATTERNS RECONSTRUCTION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Single-cell sequencing reveals cellular heterogeneity but not cell localization. However, by combining single-cell transcriptomic data with a reference atlas of a small set of genes, it would be possible to predict the position of individual cells and reconstruct the spatial expression profile of thousands of genes reported in the single-cell study. To develop new algorithms for this purpose, the Dialogue for Reverse Engineering Assessments and Methods (DREAM) consortium organized a crowd-sourced competition known as DREAM Single Cell Transcriptomics Challenge (SCTC). In the spirit of this framework, we describe here the proposed procedures for adequate reference genes selection, and an iterative procedure to predict spatial expression profile of other genes.
Fil: Alonso, Andrés Mariano. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús). Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús); Argentina
Fil: Carrea, Alejandra. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Diambra, Luis Anibal. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
description Single-cell sequencing reveals cellular heterogeneity but not cell localization. However, by combining single-cell transcriptomic data with a reference atlas of a small set of genes, it would be possible to predict the position of individual cells and reconstruct the spatial expression profile of thousands of genes reported in the single-cell study. To develop new algorithms for this purpose, the Dialogue for Reverse Engineering Assessments and Methods (DREAM) consortium organized a crowd-sourced competition known as DREAM Single Cell Transcriptomics Challenge (SCTC). In the spirit of this framework, we describe here the proposed procedures for adequate reference genes selection, and an iterative procedure to predict spatial expression profile of other genes.
publishDate 2019
dc.date.none.fl_str_mv 2019-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/129011
Alonso, Andrés Mariano; Carrea, Alejandra; Diambra, Luis Anibal; Prediction of cell position using single-cell transcriptomic data: an iterative procedure; F1000 Research Ltd; F1000Research; 8; 1775; 10-2019; 1-7
2046-1402
CONICET Digital
CONICET
url http://hdl.handle.net/11336/129011
identifier_str_mv Alonso, Andrés Mariano; Carrea, Alejandra; Diambra, Luis Anibal; Prediction of cell position using single-cell transcriptomic data: an iterative procedure; F1000 Research Ltd; F1000Research; 8; 1775; 10-2019; 1-7
2046-1402
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.12688/f1000research.20715.1
info:eu-repo/semantics/altIdentifier/url/https://f1000research.com/articles/8-1775/v1
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv F1000 Research Ltd
publisher.none.fl_str_mv F1000 Research Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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