A single-cell transcriptional gradient in human cutaneous memory T cells restricts Th17/Tc17 identity
Authors/Creators
Description
In our manuscript, we utilized scRNA-seq libraries we generated from:
-8 human psoriatic skin samples and 7 healthy control skin samples (ZIST.rds)
-3 human psoriatic skin samples before and after tildrakizumab treatment (three_tildra_Trm1.rds)
These *rds files are the Seurat objects for these data sets post-filtering and integration. For raw sequencing data corresponding to these samples, access can be found under accession number EGA: S00001005271.
We also utilized bulk RNAseq data generated from CRISPR-Cas9 knockout of ZFP36L2 in human CD4 T cells from 3 different donors. The count matrices for each of these individual samples is uploaded here alongside a key explaining what each of the samples are with filenames that also correspond to the raw fastq files submitted at the European Genome-Phenome Archive (EGA), under accession number EGA: S00001005271. There are two replicates for each sample.
All methods underlying the generation and analysis of these datasets can be found in the original manuscript:
Cook CP, Taylor M, Liu Y, et al. A single-cell transcriptional gradient in human cutaneous memory T cells restricts Th17/Tc17 identity. Cell Rep Med. 2022;3(8):100715. doi:10.1016/j.xcrm.2022.100715
Any additional questions or information requests can be addressed to Jeffrey.cheng@ucsf.edu or cook.675@berkeley.edu