A novel method for deciphering context-specific gene programs using single-cell and spatial transcriptomics data
CoGPS
is a computational framework for characterizing context-specific gene programs within scRNA-seq and ST datasets. CoGPS
leverages directed graphs and functional gene lists to construct functional networks underlying distinct cellular and spatial contexts, which further identifies context-dependent hub genes based on the topology of networks and assigns activity levels of gene programs to individual cells or spatial locations.
You can install the released version of CoGPS with:
if (!requireNamespace("devtools", quietly = TRUE))
install.packages("devtools")
devtools::install_github("Lin-bioinfo/CoGPS")
1. Static cellular contexts (the test data can be downloaded from this drive_link.
library(CoGPS)
library(parallel)
cores = detectCores(logical = FALSE) - 1
load("CoGPS_data_sc_discrete.RData")
dat = pre_sc(x = x, label = label, modes = c("discrete"), genelist = genelist, transition_point = NULL)
cl = makeCluster(cores)
net_A = net_sc(dat$A, modes = c("discrete"), genelist = genelist, select = 1, cluster = cl, seed = 1)
cl = makeCluster(cores)
net_B = net_sc(dat$B, modes = c("discrete"), genelist = genelist, select = 1, cluster = cl, seed = 1)
CoGPS_score_A = ident_sc_score(dat$A, net_A, seed = 1)
CoGPS_score_B = ident_sc_score(dat$B, net_B, seed = 1)
CoGPS_state_A = ident_sc_state(CoGPS_score_A)
CoGPS_state_B = ident_sc_state(CoGPS_score_B)
library(CoGPS)
library(parallel)
cores = detectCores(logical = FALSE) - 1
load("CoGPS_data_sc_continuous.RData")
dat = pre_sc(x = x, label = label, modes = c("continuous"), genelist = genelist, transition_point = 20)
cl = makeCluster(cores)
net = net_sc(dat, modes = c("continuous"), genelist = genelist, select = 1, cluster = cl, seed = 1)
CoGPS_score = ident_sc_score(x, net, seed = 1)
CoGPS_state = ident_sc_state(CoGPS_score)
load("CoGPS_data_st.RData")
st_anno = pre_st(x_counts, coords, genelist, ref, cell_state, core_number = 2)
roiID = st_anno[st_anno$CoGPS_state == "High", "spot_ID"]
x_st = net_st_pre(x_data, coords, genelist, roiID, r = 60)
cl = makeCluster(cores)
net_st = net_st(x_st$dat, genelist, select = 1, cluster = cl, seed = 1)
involvedID = c(roiID, x_st$neighborID)
CoGPS_score = ident_st_score(x_impute, involvedID, net_st) # use data after imputation
CoGPS is licensed under the GNU General Public License v3.0.
Please cite the following article if you use CoGPS in your research:
Should you have any questions, please feel free to write issues for this repository or contact the author directly at [email protected].