getMarkerGenes: Marker Gene Detection

In MGFM: Marker Gene Finder in Microarray gene expression data

Description

Function to detect marker genes using microarray gene expression data sets

Usage

    getMarkerGenes(data.mat, samples2compare="all", annotate=TRUE, chip=NULL,
score.cutoff=1)

Arguments

data.mat	The microarray data matrix with probe sets corresponding to rows and samples corresponding to columns.
samples2compare	A character vector with the sample names to be compared (e.g. c("liver", "lung", "brain")). By default all samples are used.
annotate	A boolean value. If TRUE the gene symbol and the entrez gene id are shown.
chip	Chip name.
score.cutoff	A value in the interval [0,1] to filter the markers according to the specificity score. The default value is 1 (no filtering).

Details

For each marker in the output list, the probe set and the corresponding score are shown. If annotate is TRUE, the gene symbol and the entrez gene id are shown. The score is used to rank the markers according to their specificity. The score values range from 0 to 1. Values near 0 would indicate high specificity and large values closer to 1 would indicate low specificity.

Value

A list with marker genes associated with each sample type.

Author(s)

Khadija El Amrani <[e-mail]>

Examples

data("ds2.mat")
res.list <- getMarkerGenes(ds2.mat, samples2compare="all", annotate=TRUE,
chip="hgu133a", score.cutoff=1)
names(res.list)
## show the first 20 markers of liver
res.list[["liver_markers"]][1:20]

Example output

Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:base':

    expand.grid

Loading required package: annotate
Loading required package: XML


'select()' returned 1:many mapping between keys and columns
[1] "liver_markers"  "lung_markers"   "brain_markers"  "kidney_markers"
[5] "heart_markers" 
 [1] "219466_s_at : APOA2 : 336 : 0.36"          
 [2] "205041_s_at : ORM1,ORM2 : 5004,5005 : 0.38"
 [3] "219465_at : APOA2 : 336 : 0.38"            
 [4] "205820_s_at : APOC3 : 345 : 0.39"          
 [5] "1431_at : CYP2E1 : 1571 : 0.42"            
 [6] "205477_s_at : AMBP : 259 : 0.44"           
 [7] "204965_at : GC : 2638 : 0.45"              
 [8] "205040_at : ORM1 : 5004 : 0.45"            
 [9] "210929_s_at : AHSG : 197 : 0.45"           
[10] "208147_s_at : CYP2C8 : 1558 : 0.46"        
[11] "210049_at : SERPINC1 : 462 : 0.47"         
[12] "209975_at : CYP2E1 : 1571 : 0.48"          
[13] "209976_s_at : CYP2E1 : 1571 : 0.48"        
[14] "211298_s_at : ALB : 213 : 0.48"            
[15] "214465_at : ORM2,ORM1 : 5005,5004 : 0.48"  
[16] "219612_s_at : FGG : 2266 : 0.48"           
[17] "204534_at : VTN,SEBOX : 7448,645832 : 0.5" 
[18] "205216_s_at : APOH : 350 : 0.51"           
[19] "206350_at : APCS : 325 : 0.51"             
[20] "206697_s_at : HP : 3240 : 0.51"            

MGFM documentation built on Nov. 8, 2020, 6:44 p.m.