seasamgo/sera: Infer seqFISH expression patterns using scRNA-seq data

Integrate the expression matrices of seqFISH and scRNA-seq data to infer spatial expression patterns in three steps: normalize against sequencing-technology specific gene expression distribution differences, implement a multi-response LASSO regression for predictor gene selection and transcriptome-level estimation, determine estimable genes for the small subset of predictor genes using a local polynomial regression against the penalized coefficient L1 norm and estimate variation threshold.

Getting started

Package details

AuthorSam Tracy
MaintainerSam Tracy <>
LicenseGPL-2 | GPL-3
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
seasamgo/sera documentation built on May 14, 2019, 1:57 a.m.