Analysis of the Grant (C075) retinal epithelial cells data set

Peter Hickey https://peterhickey.org (Single Cell Open Research Endeavour (SCORE), WEHI)https://www.wehi.edu.au/people/shalin-naik/3310/score
2020-10-01

Table of Contents

Overview

In this analysis, we study a dataset of retinal epithelial cells from Kat7 (a.k.a Hbo1) knockout and wildtype mice.

After sequencing, expression was quantified by counting the number of UMIs mapped to each gene using scPipe(Tian et al. 2018). Count data for all endogeneous genes (GENCODE Release 28 (GRCm38.p6)) and spike-in transcripts (ERCC) are available in this repository.

This analysis is adapted from the Orchestrating Single-Cell Analysis with Bioconductor book.

Analysis version information

R version: R version 4.0.0 (2020-04-24)

Bioconductor version: 3.11

Tian, Luyi, Shian Su, Xueyi Dong, Daniela Amann-Zalcenstein, Christine Biben, Azadeh Seidi, Douglas J Hilton, Shalin H Naik, and Matthew E Ritchie. 2018. “ScPipe: A Flexible R/Bioconductor Preprocessing Pipeline for Single-Cell Rna-Sequencing Data.” PLoS Computational Biology 14 (8): e1006361. https://www.ncbi.nlm.nih.gov/pubmed/30096152.