Function to convert a single-cell RNAseq matrix into a format
that can be used with runDWLSDeconv.
makeSignMatrixDWLSfromMatrix(matrix, sign_gene, cell_type_vector)matrix
sign_gene <- c(
"Bcl11b", "Lmo1", "F3", "Cnih3", "Ppp1r3c", "Rims2", "Gfap",
"Gjc3", "Chrna4", "Prkcd", "Prr18", "Grb14", "Tprn", "Clic1", "Olig2",
"Hrh3", "Tmbim1", "Carhsp1", "Tmem88b", "Ugt8a", "Arpp19", "Lamp5",
"Galnt6", "Hlf", "Hs3st2", "Tbr1", "Myl4", "Cygb", "Ttc9b", "Ipcef1"
)
sign_matrix <- matrix(rnorm(length(sign_gene) * 3), nrow = length(sign_gene))
rownames(sign_matrix) <- sign_gene
colnames(sign_matrix) <- c("cell_type1", "cell_type2", "cell_type3")
makeSignMatrixDWLSfromMatrix(
matrix = sign_matrix, sign_gene = sign_gene,
cell_type_vector = c("cell_type1", "cell_type2", "cell_type3")
)
#> cell_type1 cell_type2 cell_type3
#> Bcl11b -1.64257407 0.90291727 0.02982167
#> Lmo1 2.02928247 -0.81955398 -0.77565402
#> F3 0.24360567 -0.95983883 -0.22814752
#> Cnih3 -2.35833666 -0.47480058 -0.76710650
#> Ppp1r3c -1.00645782 0.53929337 -1.11617280
#> Rims2 0.67346027 -0.45319591 -1.24755320
#> Gfap 1.29235280 0.44509654 0.83254377
#> Gjc3 0.35618189 -0.84227927 0.30207156
#> Chrna4 0.65555144 0.42305442 -0.16425900
#> Prkcd 1.01485045 -0.61068476 -0.47329667
#> Prr18 -0.58862234 -1.59440717 -0.53683976
#> Grb14 -1.62067143 -0.47307136 -0.91952542
#> Tprn 0.04751469 -1.30061850 -0.04908513
#> Clic1 0.41265615 -0.11167877 -1.20330111
#> Olig2 1.13074690 -0.85096053 1.19473790
#> Hrh3 0.30106074 -0.93295206 -0.14523127
#> Tmbim1 0.93029226 -0.53460649 -0.47618742
#> Carhsp1 0.25679344 0.55789258 0.70669714
#> Tmem88b 0.90211498 1.41349017 -0.61837738
#> Ugt8a 0.74393878 0.83334830 -0.33495243
#> Arpp19 -0.19743101 -1.63099107 -0.45806234
#> Lamp5 -1.49194895 0.71657799 -1.15262324
#> Galnt6 -0.67613389 0.81195379 -0.32099219
#> Hlf -0.81197767 1.33243058 0.09848058
#> Hs3st2 -2.00073772 -1.90780613 0.07321805
#> Tbr1 0.68826832 0.98222701 -0.66243628
#> Myl4 -0.02155129 -0.09247253 -0.77793802
#> Cygb -0.48591156 1.08716987 -1.83601415
#> Ttc9b 0.02259776 0.49534079 -0.37544750
#> Ipcef1 1.11456689 -0.30432444 -0.75422518