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ZENODO
Software . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Software . 2021
License: CC BY
Data sources: ZENODO
Claim

Population-scale single-cell eQTL mapping identifies cell type specific genetic control of autoimmune disease

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 09 Jul 2021 English Publisher:Zenodo
Authors: Seyhan Yazar; Jose Alquicira Hernandez;
Code repository: https://github.com/powellgenomicslab/onek1k_phase1/tree/v1

doi: 10.5281/zenodo.5084396

Population-scale single-cell eQTL mapping identifies cell type specific genetic control of autoimmune disease

Abstract

This repository contains the code to analyze the OneK1K data for the phase 1 to perform eQTL mapping from 14 immune cell type populations as part of the manuscript "Population-scale single-cell eQTL mapping identifies cell type specific genetic control of autoimmune disease" Scripts are categorized according to each step/subheading from the methods section of the manuscript. All code is also available on Github: https://github.com/powellgenomicslab/onek1k_phase1

Related Organizations
Keywords

autoimmune-disease, single-cell, eQTL, cellular-genomics, colocalization, statistical-genetics

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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