BMC BioinformaticsBioinformaticsPeer-reviewed journal article
SCeQTL: an R package for identifying eQTL from single-cell parallel sequencing data
Abstract
SummaryWith the development of single-cell sequencing technologies, parallel sequencing the transcriptome and genome is becoming available and will bring us the opportunity to uncover association between genotype and phenotype at single-cell level. Due to the special characteristics of single-cell sequencing data, new method is needed to identify eQTL from single-cell data. We developed an R package SCeQTL that uses zero-inflated negative binomial regression to do eQTL analysis on single-cell data. It can distinguish two type of gene-expression differences among different genotype groups. It can also be used for finding gene expression variations associated with other grouping factors like cell lineages or cell types.\n\nAvailabilityThe R package is available at https://github.com/XuegongLab/SCeQTL/.\n\nContactzhangxg@tsinghua.edu.cn
- Citations
- 18
- FWCI
- 0.89
- Field percentile
- top 31%
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