T cell state identifier (TCellSI) is a tool to access eight distinct T cell states including Quiescence, Regulating, Proliferation, Helper, Cytotoxicity, Progenitor exhaustion, Terminal exhaustion, and Senescence. TCellSI provides a T cell state score (TCSS) for samples using specific marker gene sets and a compiled reference spectrum of T cell states from transcriptomic data. The major algorithm of TCellSI is shown as follows:
You can install the development version of TCellSI by:
# install.packages("devtools")
devtools::install_github("VyvyanYjm/TCellSI")
library(TCellSI)
#sample_expression: Complete gene expression data.frame in TPM format by log2-transformed RNA-seq data.
sample_expression <- TCellSI::exampleSample
# sample_expression
# SRR5088825 SRR5088828 SRR5088830
# 5_8S_rRNA 0.000000 0.000000 0.0000000
# 5S_rRNA 0.000000 0.000000 0.4346853
# 7SK 0.0c0000 0.000000 0.0000000
# A1BG 1.907599 3.284418 4.0821248
# A1BG-AS1 3.083914 2.021501 4.5169002
ResultScores <- TCSS_Calculate(sample_expression)
#output: The output of the function is a data.frame with TCSS metrics, where each row corresponds to a T cell state and each column represents a sample name.
# ResultScores
# SRR5088825 SRR5088828 SRR5088830
# Quiescence 0.6422158 0.6153140 0.5105856
# Regulating 0.4404173 0.3974391 0.1670356
# Proliferation 0.5780474 0.5761891 0.3994404
# Helper 0.5647604 0.4063729 0.2121070
# Cytotoxicity 0.6482720 0.5826073 0.1829111
# Progenitor_exhaustion 0.5905679 0.5308304 0.2482848
# Terminal_exhaustion 0.6624943 0.6222188 0.3311532
# Senescence 0.5921543 0.5725185 0.2896508
#If you want to apply this method to other cell states that interest you, you should compile a reference spectrum and prepare specific marker gene sets of your cell states. You can then calculate the scores for your cell states using the following function.
OtherScores <- CSS_Calculate(sample_expression, reference = XXX, markers = XXX)
#Forms of reference and markers look like:
#reference
#The self-constructed reference should contain log2-transformed, TPM-normalized gene expression data from RNA-seq or scRNA-seq.
# cell_state1 cell_state2 cell_state3
# DDX11L1 0.32323232 0.54567463 0.32456323
# WASH7P 0.82670591 1.89565638 1.40492732
# MIR6859-1 0.02172025 0.03816506 0.52313432
# MIR1302-2HG 0.00000000 0.00000000 0.00032302
# MIR1302-2 0.00000000 0.00000000 0.00002132
#markers: A list of multiple cell states containing specific gene sets
#The number of marker genes per cell state can vary.
#$cell_state1
#[1] "XXX" "XXX" "XXX" ...
#$cell_state2
#[1] "XXX" "XXX" "XXX" ...
#$cell_state3
#[1] "XXX" "XXX" "XXX" ...