Work

ClipperQTL: ultrafast and powerful eGene identification method

Year: 2023

Type: article

Abstract: Code used to generate the results in our manuscript.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.8259928

Authors: Zhou, Heather J., Ge, Xinzhou, Li, Jingyi Jessica

Institution: University of California, Los Angeles

Language: English

Topic: Genomics and Phylogenetic Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

OpenAlex ID: W6969207025

FWCI: 0.075

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Cited by: 1

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