Return significant genes for this grandR object
Usage
GetSignificantGenes(
data,
analysis = NULL,
regex = TRUE,
criteria = NULL,
as.table = FALSE,
use.symbols = TRUE,
gene.info = TRUE
)Arguments
- data
the grandR object
- analysis
the analysis to use, can be more than one and can be regexes (see details)
- regex
interpret analyses as regex?
- criteria
the criteria used to define what significant means; if NULL, Q<0.05 & abs(LFC)>=1 is used; can use the column names of the analysis table as variables, should be a logical or numerical value per gene (see Details)
- as.table
return a table
- use.symbols
return them as symbols (gene ids otherwise)
- gene.info
add gene infos to the output table
Details
The analysis parameter (just like for GetAnalysisTable can be a regex (that will be matched against all available analysis names). It can also be a vector (of regexes). Be careful with this, if more than one table e.g. with column LFC ends up in here, only the first is used (if criteria=LFC).
The criteria parameter can be used to define how analyses are performed. If criteria is a logical, it obtains significant genes defined by cut-offs (e.g. on q value and LFC). If it is a numerical, all genes are returned sorted (descendingly) by this value. The columns of the given analysis table(s) can be used to build this expression.
Examples
sars <- ReadGRAND(system.file("extdata", "sars.tsv.gz", package = "grandR"),
design=c(Design$Condition,Design$dur.4sU,Design$Replicate))
#> Warning: Duplicate gene symbols (n=1, e.g. MATR3) present, making unique!
sars <- subset(sars,Coldata(sars,Design$dur.4sU)==2)
sars<-LFC(sars,mode="total",contrasts=GetContrasts(sars,contrast=c("Condition","Mock")))
GetSignificantGenes(sars,criteria=LFC>1)
#> [1] "ATF3" "TUFT1" "MYSM1" "JUN" "ELF3" "ZC3H12A"
#> [7] "CYR61" "TXNIP" "POGZ" "ERRFI1" "PPP1R15B" "YOD1"
#> [13] "RHOB" "FOSL2" "NUAK2" "ABL2" "TET3" "CCNT2"
#> [19] "SERTAD2" "ZFP36L2" "RND3" "CYP1B1" "BHLHE40" "SNRK"
#> [25] "CSRNP1" "VIPR1" "RBM5" "NFKBIZ" "AMOTL2" "RAP2B"
#> [31] "HES1" "TSC22D2" "TIPARP" "CCNL1" "MSL2" "CXCL2"
#> [37] "CXCL1" "HS3ST1" "ARRDC3" "DUSP1" "EREG" "PLK2"
#> [43] "CHD1" "CXCL3" "NR3C1" "FEM1C" "BRD2" "TFAP2A"
#> [49] "PHIP" "PPP1R10" "IER3" "EGR1" "KLF10" "KMT2C"
#> [55] "DUSP4" "UGCG" "LCN2" "NFKB2" "DDIT4" "DUSP5"
#> [61] "KLF6" "JMJD1C" "WEE1" "ARHGAP32" "NEAT1" "MALAT1"
#> [67] "LRIG3" "TPT1" "NFKBIA" "RBM25" "CHD2" "NR2F2"
#> [73] "EIF4B" "RBBP6" "KDM6B" "CYP1A1" "NFAT5" "TRAF4"
#> [79] "SOX9" "KANSL1" "ZNF532" "GATA6" "NR1D1" "FOSB"
#> [85] "GDF15" "SBNO2" "BCL3" "IER2" "KMT2B" "RELB"
#> [91] "JUNB" "JUND" "PPP1R15A" "ZFP36" "RUNX1" "PARD6B"
#> [97] "ZC3H4" "ID1" "RIPK4" "NRIP1" "PIM3" "RBM39"
#> [103] "NORAD" "ORF3a" "E" "M" "ORF6" "ORF7a"
#> [109] "ORF7b" "ORF8" "N" "ORF10" "ORF1ab" "S"