Leveraging the cell lineage to predict cell-type specificity of regulatory variation from bulk genomics.
cell lineage
cell type
eQTL
Journal
Genetics
ISSN: 1943-2631
Titre abrégé: Genetics
Pays: United States
ID NLM: 0374636
Informations de publication
Date de publication:
15 04 2021
15 04 2021
Historique:
received:
20
12
2020
accepted:
12
01
2021
pubmed:
19
3
2021
medline:
23
9
2021
entrez:
18
3
2021
Statut:
ppublish
Résumé
Recent computational methods have enabled the inference of the cell-type-specificity of eQTLs based on bulk transcriptomes from highly heterogeneous tissues. However, these methods are limited in their scalability to highly heterogeneous tissues and limited in their broad applicability to any cell-type specificity of eQTLs. Here we present and demonstrate Cell Lineage Genetics (CeL-Gen), a novel computational approach that allows inference of eQTLs together with the subsets of cell types in which they have an effect, from bulk transcriptome data. To obtain improved scalability and broader applicability, CeL-Gen takes as input the known cell lineage tree and relies on the observation that dynamic changes in genetic effects occur relatively infrequently during cell differentiation. CeL-Gen can therefore be used not only to tease apart genetic effects derived from different cell types but also to infer the particular differentiation steps in which genetic effects are altered.
Identifiants
pubmed: 33734353
pii: 6126814
doi: 10.1093/genetics/iyab016
pmc: PMC8049554
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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