Analysis of the Pellicci gamma-delta T-cell data set

Peter Hickey https://peterhickey.org (Single Cell Open Research Endeavour (SCORE), WEHI)https://www.wehi.edu.au/people/shalin-naik/3310/score , William Ho (Single Cell Open Research Endeavour (SCORE), WEHI)https://www.wehi.edu.au/people/rory-bowden/4536/wehi-advanced-genomics-facility
2021-09-29

Overview

Analysis accompanying paper ‘Human Vγ9Vδ2+ T cells develop within the postnatal thymus via a three-stage pathway defined by distinct molecular and cellular changes.’ Please see https://wehiscore.github.io/C094_Pellicci for the HTML version of this analysis report.

After sequencing, expression was quantified by counting the number of UMIs mapped to each gene using scPipe (Tian et al. 2018); see code/scPipe.R. Count data for all endogenous genes (GENCODE Release vM18: GRCm38.p6) and spike-in transcripts (ERCC) are available in this repository.

This analysis is adapted from the simpleSingleCell workflow as well as the Orchestrating Single-Cell Analysis with Bioconductor book.

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

Analysis version information

R version: R version 4.0.3 (2020-10-10)

Bioconductor version: 3.12

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.

References