Posts Tagged ‘eqtl’
New large-scale QTL cohort
September 28, 2024Quantitative GWAS & QTL studies
February 25, 2023Primer
Published: 25 January 2023
Molecular quantitative trait loci
François Aguet, Kaur Alasoo, Yang I. Li, Alexis Battle, Hae Kyung Im, Stephen B. Montgomery & Tuuli Lappalainen
Nature Reviews Methods Primers volume 3, Article number: 4 (2023)
Related to the discussion about quantitative GWAS and QTL, this primer review (and in particular box 1) is helpful in clarifying the (non) difference between the two types of studies:
https://www.nature.com/articles/s43586-022-00188-6
The statistics behind quantitative GWAS and QTL studies is the same, the only main difference might be the multiple testing correction procedure.
In general, it’s more a nomenclature distinction, as the term “QTL” is often used specifically for molecular traits.
science
January 29, 2022eQTLs paper is out in Nature Genetics:
Zeng, B., Bendl, J., Kosoy, R. et al. [Panos R] Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits. Nat Genet (2022).
https://doi.org/10.1038/s41588-021-00987-9
metabrain QTL
July 17, 2021Brain expression quantitative trait locus and network analysis reveals downstream effects and putative drivers for brain-related diseases by N. de Klein et al., bioRxiv, 2021.
Second fetal brain article…splciing and expression QTL and integration with single cell with WGCNA networks
October 29, 2019https://www.sciencedirect.com/science/article/pii/S0092867419310724?dgcid=author
Rebecca L. Walker, Gokul Ramaswami, Christopher Hartl, Nicholas Mancuso, Michael J. Gandal, Luis de la Torre-Ubieta, Bogdan Pasaniuc, Jason L. Stein, Daniel H. Geschwind,
Genetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms,
Cell,
Volume 179, Issue 3,
2019,
Pages 750-771.e22,
ISSN 0092-8674,
https://doi.org/10.1016/j.cell.2019.09.021
A Genome-wide Framework for Mapping Gene Regulation via Cellular Genetic Screens. – PubMed – NCBI
June 15, 2019https://www.ncbi.nlm.nih.gov/pubmed/30612741
crisprQTL
crisprQTL mapping as a genome-wide association framework for cellular genetic screens
Molly Gasperini, Andrew J. Hill, José L. McFaline-Figueroa, Beth Martin, Cole Trapnell, Nadav Ahituv, Jay Shendure
doi: https://doi.org/10.1101/314344
Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions
December 25, 2018seems to be better for eQTLs
https://www.nature.com/articles/s41588-018-0268-8
paper on geuvadis rna-seq variant calling
February 11, 2017Calling genotypes from public RNA-sequencing data enables
identification of genetic variants that affect gene-expression levels
Patrick Deelen†,
Daria V Zhernakova†,
Mark de Haan,
Marijke van der Sijde,
Marc Jan Bonder,
Juha Karjalainen,
K Joeri van der Velde,
Kristin M Abbott,
Jingyuan Fu,
Cisca Wijmenga,
Richard J Sinke,
Morris A Swertz† and
Lude Franke†
Genotypes from…#RNAseq…enables identification of…variants, related to ASE & eQTLs
https://GenomeMedicine.biomedcentral.com/articles/10.1186/s13073-015-0152-4 Validation w/ #Geuvadis
Jclub paper
January 16, 2017The impact of #SVs on…gene expression
http://biorxiv.org/content/early/2016/06/09/055962 24k in 147 people in GTEx pilot act as causal variants in 3-7% of ~25k eQTLs
The impact of structural variation on human gene expression
Colby Chiang, Alexandra J Scott, Joe R Davis, Emily
K Tsang, Xin Li, Yungil Kim, Farhan N Damani, Liron Ganel, GTEx Consortium, Stephen B Montgomery, Alexis Battle, Donald F Conrad, Ira M Hall
doi: https://doi.org/10.1101/055962
linkstream2 microblog 