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Liis Kolberg

Researcher at University of Tartu

Publications -  14
Citations -  4585

Liis Kolberg is an academic researcher from University of Tartu. The author has contributed to research in topics: Genome-wide association study & Expression quantitative trait loci. The author has an hindex of 7, co-authored 12 publications receiving 2382 citations.

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g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update).

TL;DR: G:Profiler is now capable of analysing data from any organism, including vertebrates, plants, fungi, insects and parasites, and the 2019 update introduces an extensive technical rewrite making the services faster and more flexible.
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g:Profiler—a web server for functional interpretation of gene lists (2016 update)

TL;DR: The 2016 update of g:Profiler introduces several novel features, including transcription factor binding site predictions, Mendelian disease annotations, information about protein expression and complexes and gene mappings of human genetic polymorphisms.
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gprofiler2 -- an R package for gene list functional enrichment analysis and namespace conversion toolset g:Profiler.

TL;DR: The accompanying R package, gprofiler2, developed to facilitate programmatic access to g:Profiler computations and databases via REST API, provides an easy-to-use functionality that enables researchers to incorporate functional enrichment analysis into automated analysis pipelines written in R.
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A compendium of uniformly processed human gene expression and splicing quantitative trait loci.

TL;DR: The eQTL Catalogue as discussed by the authors is a set of gene expression quantitative trait locus (eQTL) studies published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization.
Posted ContentDOI

eQTL Catalogue: a compendium of uniformly processed human gene expression and splicing QTLs

TL;DR: The eQTL Catalogue is presented, a resource which contains quality controlled, uniformly recomputed QTLs from 21 eQtl studies, and it is found that for matching cell types and tissues, the eZTL effect sizes are highly reproducible between studies, enabling the integrative analysis of these data.