Published July 12, 2022
| Version 1.0.0
Software
Open
Data Visualization Code for "Time-resolved transcriptomics reveal diverse B cell fate trajectories in the early response to Epstein-Barr virus infection"
Description
R script for Seurat-based processing and visualization of scRNA-seq data from time-resolved early EBV infection
Code used for analysis in "Time-resolved transcriptomics reveal diverse B cell fate trajectories in the early response to Epstein-Barr virus infection." A pre-print version of this work can be found on bioRxiv: https://www.biorxiv.org/content/10.1101/2022.02.23.481342v2.full
Original scRNA data are available through the NIH Gene Expression Omnibus (GEO). Accession ID: GSE189141
Please cite accordingly if you use this code in your work, including the original citations for Seurat and Monocle3 (see Satija Lab and Trapnell Lab GitHub and websites for more info)
Files
README.md
Files
(34.9 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:548f78f5ebf8de08d784f183f760cc53
|
34.2 kB | Download |
|
md5:204e90072b6d7cf258c4913243f44608
|
708 Bytes | Preview Download |