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HTCA: a database with an in-depth characterization of the single-cell human transcriptome

Single-cell RNA-sequencing (scRNA-seq) is one of the most used single-cell omics in recent decades. The exponential growth of single-cell data has immense potential for large-scale integration and in-depth explorations that are more representative of the study population. Efforts have been made to c...

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Autores principales: Pan, Lu, Shan, Shaobo, Tremmel, Roman, Li, Weiyuan, Liao, Zehuan, Shi, Hangyu, Chen, Qishuang, Zhang, Xiaolu, Li, Xuexin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825435/
https://www.ncbi.nlm.nih.gov/pubmed/36130266
http://dx.doi.org/10.1093/nar/gkac791
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author Pan, Lu
Shan, Shaobo
Tremmel, Roman
Li, Weiyuan
Liao, Zehuan
Shi, Hangyu
Chen, Qishuang
Zhang, Xiaolu
Li, Xuexin
author_facet Pan, Lu
Shan, Shaobo
Tremmel, Roman
Li, Weiyuan
Liao, Zehuan
Shi, Hangyu
Chen, Qishuang
Zhang, Xiaolu
Li, Xuexin
author_sort Pan, Lu
collection PubMed
description Single-cell RNA-sequencing (scRNA-seq) is one of the most used single-cell omics in recent decades. The exponential growth of single-cell data has immense potential for large-scale integration and in-depth explorations that are more representative of the study population. Efforts have been made to consolidate published data, yet extensive characterization is still lacking. Many focused on raw-data database constructions while others concentrate mainly on gene expression queries. Hereby, we present HTCA (www.htcatlas.org), an interactive database constructed based on ∼2.3 million high-quality cells from ∼3000 scRNA-seq samples and comprised in-depth phenotype profiles of 19 healthy adult and matching fetal tissues. HTCA provides a one-stop interactive query to gene signatures, transcription factor (TF) activities, TF motifs, receptor–ligand interactions, enriched gene ontology (GO) terms, etc. across cell types in adult and fetal tissues. At the same time, HTCA encompasses single-cell splicing variant profiles of 16 adult and fetal tissues, spatial transcriptomics profiles of 11 adult and fetal tissues, and single-cell ATAC-sequencing (scATAC-seq) profiles of 27 adult and fetal tissues. Besides, HTCA provides online analysis tools to perform major steps in a typical scRNA-seq analysis. Altogether, HTCA allows real-time explorations of multi-omics adult and fetal phenotypic profiles and provides tools for a flexible scRNA-seq analysis.
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spelling pubmed-98254352023-01-10 HTCA: a database with an in-depth characterization of the single-cell human transcriptome Pan, Lu Shan, Shaobo Tremmel, Roman Li, Weiyuan Liao, Zehuan Shi, Hangyu Chen, Qishuang Zhang, Xiaolu Li, Xuexin Nucleic Acids Res Database Issue Single-cell RNA-sequencing (scRNA-seq) is one of the most used single-cell omics in recent decades. The exponential growth of single-cell data has immense potential for large-scale integration and in-depth explorations that are more representative of the study population. Efforts have been made to consolidate published data, yet extensive characterization is still lacking. Many focused on raw-data database constructions while others concentrate mainly on gene expression queries. Hereby, we present HTCA (www.htcatlas.org), an interactive database constructed based on ∼2.3 million high-quality cells from ∼3000 scRNA-seq samples and comprised in-depth phenotype profiles of 19 healthy adult and matching fetal tissues. HTCA provides a one-stop interactive query to gene signatures, transcription factor (TF) activities, TF motifs, receptor–ligand interactions, enriched gene ontology (GO) terms, etc. across cell types in adult and fetal tissues. At the same time, HTCA encompasses single-cell splicing variant profiles of 16 adult and fetal tissues, spatial transcriptomics profiles of 11 adult and fetal tissues, and single-cell ATAC-sequencing (scATAC-seq) profiles of 27 adult and fetal tissues. Besides, HTCA provides online analysis tools to perform major steps in a typical scRNA-seq analysis. Altogether, HTCA allows real-time explorations of multi-omics adult and fetal phenotypic profiles and provides tools for a flexible scRNA-seq analysis. Oxford University Press 2022-09-21 /pmc/articles/PMC9825435/ /pubmed/36130266 http://dx.doi.org/10.1093/nar/gkac791 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Pan, Lu
Shan, Shaobo
Tremmel, Roman
Li, Weiyuan
Liao, Zehuan
Shi, Hangyu
Chen, Qishuang
Zhang, Xiaolu
Li, Xuexin
HTCA: a database with an in-depth characterization of the single-cell human transcriptome
title HTCA: a database with an in-depth characterization of the single-cell human transcriptome
title_full HTCA: a database with an in-depth characterization of the single-cell human transcriptome
title_fullStr HTCA: a database with an in-depth characterization of the single-cell human transcriptome
title_full_unstemmed HTCA: a database with an in-depth characterization of the single-cell human transcriptome
title_short HTCA: a database with an in-depth characterization of the single-cell human transcriptome
title_sort htca: a database with an in-depth characterization of the single-cell human transcriptome
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825435/
https://www.ncbi.nlm.nih.gov/pubmed/36130266
http://dx.doi.org/10.1093/nar/gkac791
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