In githubz0r/SecretUtils: Some utils for Conos

library(conos)
library(tidyverse)
devtools::load_all('/home/larsc/SecretUtils')
library(cowplot)
library(splatter)
devtools::load_all('/home/viktor_petukhov/Copenhagen/NeuronalMaturation')
devtools::load_all('/home/viktor_petukhov/SmallProjects/scConditionDifference')
params <- readRDS('/home/larsc/data/splatter_lamp5_params.rds')

How to generate params

#epilepsy_con <- readRDS(file.path('/home/larsc/data/10x_preproced_graphed.rds'))
#epilepsy_annot <- readRDS(file.path('/home/demharters/R/projects/UPF9_14_17_19_22_23_24_32_33/metadata_10x_final.rds'))
#epilepsy_annot$cellid <- rownames(epilepsy_annot)
#raw_cm <- RbindRaw(epilepsy_con)
#sub_matrices <- GetSubMatrices(epilepsy_annot$subtype, epilepsy_annot$cellid, epilepsy_annot$condition, raw_cm, 
                               #colnames(raw_cm), avg=F)
#testmat <- sub_matrices$healthy$L2_Lamp5 %>% as.matrix %>% removezerocols %>% Matrix::t()
#params <- splatEstimate(testmat)

Initiate variables for the simulations

group_prob <- rep(1/6, 6)
de_prob <- c(0.0, 0.0, 0.2, 0.3, 0.4, 0.5)
ncellvec <- c(30, 100, 200, 500, 1000)
ngenevec <- c(100, 1000, 5000, 10000, 20000)
de_prob <- c(0.0, 0.0, 0.2, 0.3, 0.4, 0.5)
liblocvec <- c(6.5, 7, 7.5, 8, 8.5)
seeds <- c(22071, 666, 9001)
leiden_resolutions <- c(1, 1.5, 2, 2.5)
distances <- list('paga', 'correlation.distance', 'jensen_shannon', 'CMD', 'euclidean', 'knncor.z', 'knncor.z.med', 'entropy')

Create the data (this takes a while, so we make pre-make some sims and save them)

#cell_sim <- MakeSimsAllSeeds(seeds, ncellvec, de_prob, 'ncell', make.p2 = T, n.cl.tsne=30, n.cl.sim=3)
#gene_sim <- MakeSimsAllSeeds(seeds, ngenevec, de_prob, 'ngenes', make.p2 = T, n.cl.tsne=30, n.cl.sim=3)
#libloc_sim <- MakeSimsAllSeeds(seeds, liblocvec, de_prob, 'lib.loc', make.p2 = T, n.cl.tsne=30, n.cl.sim=3)

# save these for convnience
#saveRDS(cell_sim, '/home/larsc/data/splatter_data/final_script_data/cell_sim_final.rds')
#saveRDS(gene_sim, '/home/larsc/data/splatter_data/final_script_data/gene_sim_final.rds')
#saveRDS(libloc_sim, '/home/larsc/data/splatter_data/final_script_data/libloc_sim_final.rds')

cell_sim <- readRDS('/home/larsc/data/splatter_data/final_script_data/cell_sim_final.rds')
gene_sim <- readRDS('/home/larsc/data/splatter_data/final_script_data/gene_sim_final.rds')
libloc_sim <- readRDS('/home/larsc/data/splatter_data/final_script_data/libloc_sim_final.rds')

Create data frames for the distances (takes a while, especially the entropy, so we pre-make it)

#dfs_per_distance <- AllDistsDfs(list(cell_sim, gene_sim, libloc_sim), list('ncell', 'ngenes', 'lib.loc'),
                                #distances, avg.meds=T, leiden.resolutions=leiden_resolutions)
#saveRDS(dfs_per_distance, '/home/larsc/data/splatter_data/final_script_data/dfs_per_distance.rds')
dfs_per_distance <- readRDS('/home/larsc/data/splatter_data/final_script_data/dfs_per_distance.rds')

Create plots and make a grid

all_plots <- doPlotsPerFactor(dfs_per_distance, jitter=T, geom.smooth=T)
grid_all <- CreateGrid(all_plots, leiden_resolutions)
pdf(file='/home/larsc/grid_of_grids.pdf',width=15,height=40)
grid_all
dev.off()