Question

Error in exprs(object)[index, , drop = FALSE] : subscript out of bounds while using GCRMA

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deepak.juit • 0

@deepakjuit-17132

Last seen 5.6 years ago

Hello,

I am getting the error while using gcrma on wheat micro array data.

> data

size of arrays=1164x1164 features (20 kb)
cdf=wheat (61290 affyids)
number of samples=6
number of genes=61290
annotation=wheat
notes=

> dim(exprs(x))

1354896 6

> pData(x)
sample treatment
CL_C_R_46.CEL CL_C_R_1 control
CL_C_R_47.CEL CL_C_R_2 control
CL_C_R_48.CEL CL_C_R_3 control
CL_S_R_40.CEL CL_S_R_1 stress
CL_S_R_41.CEL CL_S_R_2 stress
CL_S_R_42.CEL CL_S_R_3 stress

> head(exprs(x))
CL_C_R_46.CEL CL_C_R_47.CEL CL_C_R_48.CEL CL_S_R_40.CEL CL_S_R_41.CEL
1 245 198 176 298 188
2 7596 6592 8318 6832 7159
3 309 257 292 319 250
4 7727 6857 8359 7294 7538
5 224 204 98 137 181
6 153 104 135 192 84
CL_S_R_42.CEL
1 204
2 6404
3 252
4 6578
5 177
6 98

As there are index in place of probe ids.

> head(featureNames(data))
[1] "AFFX-BioB-3_at" "AFFX-BioB-5_at" "AFFX-BioB-M_at" "AFFX-BioC-3_at" "AFFX-BioC-5_at"
[6] "AFFX-BioDn-3_at"
> length(featureNames(data))
[1] 61290

when I do normalization using gcrna i encounterd following error

> my.affinity.info = compute.affinities2("wheat")
Computing affinities.Done.
Warning message:
xy2i is deprecated and will be removed in the next BioC release.
Use xy2indices in the affy package instead.

my.affinity.info looks like below.. i think there is an error as size of array is 0 x 0

> my.affinity.info
AffyBatch object
size of arrays=0x0 features (16 kb)
cdf=wheat (61290 affyids)
number of samples=1
number of genes=61290
annotation=

> data.gcrma = gcrma(x,affinity.info=my.affinity.info)
Adjusting for optical effect......Done.
Error in exprs(object)[index, , drop = FALSE] : subscript out of bounds

Please help to solve the problem. any help appreciated.

> sessioninfo()

R version 3.5.0 (2018-04-23)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows Server 2008 R2 x64 (build 7601) Service Pack 1

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252

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

other attached packages:
[1] simpleaffy_2.56.0 gcrma_2.52.0 genefilter_1.62.0 affy_1.58.0 Biobase_2.40.0
[6] BiocGenerics_0.26.0 wheatcdf_2.18.0

loaded via a namespace (and not attached):
[1] Rcpp_0.12.18 AnnotationDbi_1.42.1 XVector_0.20.0 splines_3.5.0
[5] zlibbioc_1.26.0 IRanges_2.14.10 bit_1.1-14 lattice_0.20-35
[9] xtable_1.8-2 blob_1.1.1 tools_3.5.0 grid_3.5.0
[13] DBI_1.0.0 survival_2.42-6 yaml_2.2.0 bit64_0.9-7
[17] digest_0.6.15 preprocessCore_1.42.0 affyio_1.50.0 Matrix_1.2-14
[21] bitops_1.0-6 S4Vectors_0.18.3 RCurl_1.95-4.11 memoise_1.1.0
[25] RSQLite_2.1.1 compiler_3.5.0 BiocInstaller_1.30.0 Biostrings_2.48.0
[29] XML_3.98-1.16 stats4_3.5.0 annotate_1.58.0

gcrma wheatcdf cdf • 1.7k views

ADD COMMENT • link updated 5.6 years ago by James W. MacDonald 65k • written 5.6 years ago by deepak.juit • 0

score 0 · Answer 1 · 2018-09-04

If you read the help page for compute.affinities, there is this:

 Use 'compute.affinities2' if there are no MM probes.

But you are using the Wheat Genome Array, which does have MM probes! Also, do note that you don't have to compute the affinities separately (particularly if you aren't doing anything but the default), and can just use gcrma directly.

> dat <- ReadAffy()
> eset <- gcrma(dat)
Adjusting for optical effect............Done.
Computing affinities.Done.
Adjusting for non-specific binding............Done.
Normalizing
Calculating Expression
> eset
ExpressionSet (storageMode: lockedEnvironment)
assayData: 61290 features, 12 samples
  element names: exprs
protocolData
  sampleNames: GSM675415.CEL.gz GSM675416.CEL.gz ... GSM675426.CEL.gz
    (12 total)
  varLabels: ScanDate
  varMetadata: labelDescription
phenoData
  sampleNames: GSM675415.CEL.gz GSM675416.CEL.gz ... GSM675426.CEL.gz
    (12 total)
  varLabels: sample
  varMetadata: labelDescription
featureData: none
experimentData: use 'experimentData(object)'
Annotation: wheat

> sessionInfo()
R version 3.5.0 (2018-04-23)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17134)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] stats4    parallel  stats     graphics  grDevices utils     datasets
[8] methods   base     

other attached packages:
 [1] GEOquery_2.48.0      wheatprobe_2.18.0    AnnotationDbi_1.42.1
 [4] IRanges_2.14.10      S4Vectors_0.18.3     wheatcdf_2.18.0     
 [7] gcrma_2.52.0         affy_1.58.0          Biobase_2.40.0      
[10] BiocGenerics_0.26.0

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.18          BiocInstaller_1.30.0  compiler_3.5.0       
 [4] pillar_1.3.0          XVector_0.20.0        bindr_0.1.1          
 [7] tools_3.5.0           zlibbioc_1.26.0       digest_0.6.15        
[10] bit_1.1-14            RSQLite_2.1.1         memoise_1.1.0        
[13] preprocessCore_1.42.0 tibble_1.4.2          pkgconfig_2.0.1      
[16] rlang_0.2.1           DBI_1.0.0             curl_3.2             
[19] bindrcpp_0.2.2        xml2_1.2.0            dplyr_0.7.6          
[22] hms_0.4.2             Biostrings_2.48.0     bit64_0.9-7          
[25] tidyselect_0.2.4      glue_1.3.0            R6_2.2.2             
[28] limma_3.36.2          tidyr_0.8.1           readr_1.1.1          
[31] purrr_0.2.5           blob_1.1.1            magrittr_1.5         
[34] splines_3.5.0         assertthat_0.2.0      crayon_1.3.4         
[37] affyio_1.50.0