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Haemopedia RNA-seq: a database of gene expression during haematopoiesis in mice and humans

Citation

Choi, J and Baldwin, TM and Wong, M and Bolden, JE and Fairfax, KA and Lucas, EC and Cole, R and Biben, C and Morgan, C and Ramsay, KA and Ng, AP and Kauppi, M and Corcoran, LM and Shi, W and Wilson, N and Wilson, MJ and Alexander, WS and Hilton, DJ and de Graaf, CA, Haemopedia RNA-seq: a database of gene expression during haematopoiesis in mice and humans, Nucleic Acids Research, 47, (D1) pp. D780-D785. ISSN 0305-1048 (2019) [Refereed Article]


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Copyright Statement

Copyright The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

DOI: doi:10.1093/nar/gky1020

Abstract

During haematopoiesis, haematopoietic stem cells differentiate into restricted potential progenitors before maturing into the many lineages required for oxygen transport, wound healing and immune response. We have updated Haemopedia, a database of gene-expression profiles from a broad spectrum of haematopoietic cells, to include RNA-seq gene-expression data from both mice and humans. The Haemopedia RNA-seq data set covers a wide range of lineages and progenitors, with 57 mouse blood cell types (flow sorted populations from healthy mice) and 12 human blood cell types. This data set has been made accessible for exploration and analysis, to researchers and clinicians with limited bioinformatics experience, on our online portal Haemosphere: https://www.haemosphere.org. Haemosphere also includes nine other publicly available high-quality data sets relevant to haematopoiesis. We have added the ability to compare gene expression across data sets and species by curating data sets with shared lineage designations or to view expression gene vs gene, with all plots available for download by the user.

Item Details

Item Type:Refereed Article
Research Division:Biological Sciences
Research Group:Bioinformatics and computational biology
Research Field:Bioinformatic methods development
Objective Division:Health
Objective Group:Clinical health
Objective Field:Diagnosis of human diseases and conditions
UTAS Author:Fairfax, KA (Dr Kirsten Fairfax)
ID Code:134787
Year Published:2019
Web of Science® Times Cited:65
Deposited By:Menzies Institute for Medical Research
Deposited On:2019-09-05
Last Modified:2019-10-16
Downloads:21 View Download Statistics

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