pSI.list extracts, for each cell type/sample and each of the four
standard pSI thresholds (0.05, 0.01, 0.001 and 0.0001), the genes whose pSI
values fall below the threshold, i.e. the genes specific to that cell type.
Arguments
- pSIs
data frame output from
specificity.index, with one column per cell type/sample and genes as rows.- write.csv
logical. If
TRUE, one CSV file per threshold (pSi_0.05.csv,pSi_0.01.csv,pSi_0.001.csv,pSi_1e-04.csv) is written to the current working directory. The default isFALSE: since pSI 1.2.0 nothing is written unless you ask for it.
Value
A named list of four data frames (pSi_0.0001,
pSi_0.001, pSi_0.01, pSi_0.05), one per pSI
threshold. Each has one column per cell type/sample, named
<sample>_<threshold>, containing the symbols of the genes with pSI
below that threshold, padded with NA.
Details
Gene symbols are converted to upper case for consistency in downstream
analysis. Within each data frame the columns hold different numbers of genes
and are padded with NA to equal length.
See also
pSI.count for the counts alone,
candidate.overlap to intersect these lists with a candidate
gene list.
Examples
##load sample pSI output
data(sample.data)
##List the genes specific to each cell type/sample type across all pSI thresholds
pSI.out.list <- pSI.list(pSIs=sample.data$pSI.output)
names(pSI.out.list)
#> [1] "pSi_0.0001" "pSi_0.001" "pSi_0.01" "pSi_0.05"
head(pSI.out.list$pSi_0.01)
#> Amygdala.Young.Adulthood_0.01 Cerebellum.Young.Adulthood_0.01
#> 1 NA CYP26B1
#> 2 NA ETV1
#> 3 NA PAX6
#> 4 NA TSPAN9
#> 5 NA TMEM159
#> 6 NA ZIC2
#> Cortex.Young.Adulthood_0.01 Hippocampus.Young.Adulthood_0.01
#> 1 NUAK1 FBLN1
#> 2 MEF2C CABP7
#> 3 NLK ICAM5
#> 4 CHGA SOD3
#> 5 NCALD FOLR1
#> 6 STX1A TTR
#> Striatum.Young.Adulthood_0.01 Thalamus.Young.Adulthood_0.01
#> 1 TAC1 DBNDD1
#> 2 ACTN2 OPN3
#> 3 TESC PTPN3
#> 4 RASD2 SLC17A6
#> 5 COCH NEFH
#> 6 C20ORF27 HRH3