inst/doc/ontoProc.R

In ontoProc: processing of ontologies of anatomy, cell lines, and so on

## ----setup--------------------------------------------------------------------
suppressPackageStartupMessages({
library(knitr)
library(ontoProc)
go = getGeneOnto()
cl = getCellOnto()
pr = getPROnto()
library(ontologyPlot)
library(BiocStyle)
})

## ----lksco--------------------------------------------------------------------
kable(packDesc2019)

## ----lklk---------------------------------------------------------------------
kable(stab <- seur3kTab())

## ----lklklk-------------------------------------------------------------------
library(ontoProc)
cl = getCellOnto()
onto_plot2(cl, stab$tag)

## ----lkfa---------------------------------------------------------------------
kable(CLfeats(cl, "CL:0002531"))

## ----lksy---------------------------------------------------------------------
kable(sdf <- as.data.frame(sym2CellOnto("ITGAM", cl, pr)))
table(sdf$cond)
kable(as.data.frame(sym2CellOnto("FOXP3", cl, pr)))

## ----lksig--------------------------------------------------------------------
sigels = c("CL:X01"="GRIK3", "CL:X02"="NTNG1", "CL:X03"="BAGE2",
             "CL:X04"="MC4R", "CL:X05"="PAX6", "CL:X06"="TSPAN12", 
             "CL:X07"="hSHISA8", "CL:X08"="SNCG", "CL:X09"="ARHGEF28", 
             "CL:X10"="EGF")

## ----lkdfff-------------------------------------------------------------------
cs = cyclicSigset(sigels)
dim(cs)
cs[c(1:5,9:13),]
table(cs$cond)

## ----lklk1--------------------------------------------------------------------
 makeIntnProlog = function(id, ...) {
 # make type-specific prologs as key-value pairs
     c(  
       sprintf("id: %s", id),
       sprintf("name: %s-expressing cortical layer 1 interneuron, human", ...),
       sprintf("def: '%s-expressing cortical layer 1 interneuron, human described via RNA-seq observations' [PMID 29322913]", ...),
       "is_a: CL:0000099 ! interneuron",
       "intersection_of: CL:0000099 ! interneuron")
 }

## ----doterm-------------------------------------------------------------------
pmap = c("hasExp"="has_expression_of", lacksExp="lacks_expression_of")
head(unlist(tms <- ldfToTerms(cs, pmap, sigels, makeIntnProlog)), 20)

## ----lkmap--------------------------------------------------------------------
hpca_map = read.csv(system.file("extdata/hpca.csv", package="ontoProc"), strings=FALSE)
head(hpca_map)

## ----doren--------------------------------------------------------------------
names(hpca_map) = c("informal", "formal")  # obligatory for now

## ----gethpca, eval=TRUE-------------------------------------------------------
library(SingleCellExperiment)
library(celldex)
hpca_sce = HumanPrimaryCellAtlasData()

## ----dobind, eval=TRUE--------------------------------------------------------
hpca_sce = bind_formal_tags(hpca_sce, "label.fine", hpca_map)
length(unique(hpca_sce$label.ont))

## ----justna, eval=TRUE--------------------------------------------------------
length(xx <- which(is.na(hpca_sce$label.ont)))
if (length(xx)>0) print(colData(hpca_sce)[xx,])
sum(hpca_sce$label.ont == "", na.rm=TRUE) # iPS and BM

## ----dosub, eval=TRUE---------------------------------------------------------
cell_onto = ontoProc::getCellOnto()
hpca_mono = subset_descendants( hpca_sce, cell_onto, "^monocyte$" )
table(hpca_mono$label.fine)
table(hpca_mono$label.ont) # not much diversity
hpca_tcell = subset_descendants( hpca_sce, cell_onto, "^T cell$" )
table(hpca_tcell$label.fine)
table(hpca_tcell$label.ont) # 
uu = unique(hpca_tcell$label.ont)
onto_plot2(cell_onto, uu)