This repository contains the analysis code pipeline to generate PEER factors from pseudo-bulk data and perform eQTL association analysis as part of the manuscript "Pitfalls and opportunities for applying latent variables in single-cell eQTL analyses"
Scripts are listed by the order in the methods section of the manuscript:
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Extract the whole OneK1K dataset from *.RDS and subgroup into 14 cell types
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Generate the pseudo-bulk mean matrix
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Generate PEER factors with 13 QC options
a. Extra information of runtime and nr of iterations
b. Make new covariate files
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Run sensitivity test by MatrixeQTL
a. Merge results
b. Summarize and nr of eQTL and eGenes
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Down-sampling analysis
All code is also available on Github: https://github.com/powellgenomicslab/PEER_factors
Angli Xue, Seyhan Yazar, Drew Neavin, Joseph E. Powell. Pitfalls and opportunities for applying latent variables in single-cell eQTL analyses. Genome Biology. 2023. [Full text]
For questions, please email us at Angli Xue (a.xue@garvan.org.au) or Joseph E. Powell (j.powell@garvan.org.au)