Phenotypic heterogeneity in cell populations has been shown to play critical roles in determining biologically and clinically significant phenotypes. The goal of this project is to identify robustness QTLs, loci in the human genome that are associated with within-individual variation in gene expression levels.
We collected single cell RNA-seq data from YRI invididuals using the C1 platform. We pooled and sequenced each C1 chip on an Illumina HiSeq 2500.
We matched samples to individuals using verifyBamID.
We filtered low quality samples and both over- and lowly-expressed genes for downstream analysis.
We performed dimensionality reduction on the quality-controlled samples and genes to identify the remaining major sources of variation.
We estimated means and dispersions per individual per gene using zero-inflated negative binomial models.
We derived continuous phenotypes from the fitted models and mapped QTLs using QTLtools.
We estimated the power to detect dispersion effects as a function of the single cell experiment size.
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