[R] R: [BioC] samr - extract genes from siggenes.table

Manca Marco (PATH) m.manca at maastrichtuniversity.nl
Wed Feb 9 17:54:14 CET 2011



I am not sure about this... I think they have logFC larger than 2... you are simply seeing them in scientific notation.

Why don't you try setting the option scipen (penalty for scientific notation) "on the high side"?

Something like:

> options(scipen = 50)

should be more than enough... 

Anyway, most likely other people can give you better hints.

All the best, Marco

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Marco Manca, MD
University of Maastricht
Faculty of Health, Medicine and Life Sciences (FHML)
Cardiovascular Research Institute (CARIM)

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Da: bioconductor-bounces at r-project.org [bioconductor-bounces at r-project.org] per conto di Assa Yeroslaviz [frymor at gmail.com]
Inviato: mercoledì 9 febbraio 2011 17.35
A: bioconductor; R help forum
Oggetto: [BioC] samr - extract genes from siggenes.table

Hi BioC user,

I have a problem extracting the gene set I would like to work with.
Here is I  work with my data:
normData <- read.delim("normalizedData.txt",sep ="\t")

######### two class unpaired comparison
# y must take values 1,2
classes <- c(-1,-2,1,2)

#prepere the data for the samr analysis
data.x <-as.matrix(normData[,8:11])

    d=list(x=data.x,y=classes,
geneid=as.character(normData[,1]),genenames=as.character(normData[,1]),
logged2=TRUE)
    samr.obj<-samr(d,  resp.type="Two class paired", nperms=100)

delta.table <- samr.compute.delta.table(samr.obj)
delta=0.4
siggenes.table<-samr.compute.siggenes.table(samr.obj,delta, d,
delta.table,min.foldchange=2)


genes.up     <- as.data.frame(siggenes.table$genes.up)
genes.down     <- as.data.frame(siggenes.table$genes.lo)

the data set I am working with has four column of two experiments. when
running the samr.compute.siggenes.table command I get
> str(siggenes.table)
List of 5
 $ genes.up           : chr [1:9769, 1:8] "6587" "865" "22929" "10172" ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : NULL
  .. ..$ : chr [1:8] "Row" "Gene ID" "Gene Name" "Score(d)" ...
 $ genes.lo           : chr [1:10788, 1:8] "10836" "22277" "1243" "10509"
...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : NULL
  .. ..$ : chr [1:8] "Row" "Gene ID" "Gene Name" "Score(d)" ...
 $ color.ind.for.multi: NULL
 $ ngenes.up          : int 9769
 $ ngenes.lo          : int 10788

So I guess I have 9769 up-regulated  and 10788 down-regulated genes. The
problem is, that not all of them are above 2fold:

> head(siggenes.table$genes.up)
     Row     Gene ID           Gene Name         Score(d)
[1,] "6587"  "NM_001142426_at" "NM_001142426_at" "670.084615384572"
[2,] "865"   "NM_000946_at"    "NM_000946_at"    "581.731543624152"
[3,] "22929" "NM_147134_at"    "NM_147134_at"    "469.481132075439"
[4,] "10172" "NM_003640_at"    "NM_003640_at"    "296.630872483217"
[5,] "10956" "NM_004484_at"    "NM_004484_at"    "284.233163028334"
[6,] "28444" "XM_001125699_at" "XM_001125699_at" "281.629310344832"
     Numerator(r) Denominator(s+s0)   Fold Change
[1,] "435.555"    "0.650000000000041" "*1.30352619041372e+131*"
[2,] "433.39"     "0.745000000000012" "2.90663046260321e+130"
[3,] "248.825"    "0.530000000000037" "8.01288059495468e+74"
[4,] "220.99"     "0.745000000000012" "3.34671508906627e+66"
[5,] "3059.77"    "10.7649999999999"  "Inf"
[6,] "163.345"    "0.579999999999991" "*1.48506219251034e+49*"
     q-value(%)
[1,] "0"
[2,] "0"
[3,] "0"
[4,] "1.95405681104834"
[5,] "1.95405681104834"
[6,] "1.95405681104834"
 @What do I need the parameter min.foldchage if it is not a filter to
extract genes with a fold induction value lower than 2?

I would like to know how do I extract a subset of matrix from inside a list?
my siggenes.table is a list with two matrices inside. I would like to filter
these matrices for genes with a 2fold up- and down-regulation.

Thanks
Assa

> sessionInfo()
R version 2.12.0 (2010-10-15)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] samr_1.28     impute_1.24.0

loaded via a namespace (and not attached):
[1] tools_2.12.0

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