mas5calls function doesn't work; mirna40cdf problem
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Berna • 0
@bc6afe81
Last seen 4 weeks ago
Germany
setwd("microArray/A549_ALI(1)/A549_ALI/4_tert-Butanol (22)/")
list.celfiles()
my.affy=ReadAffy()
my.calls <- mas5calls(my.affy)

This is my code and and up to my.affy it works. Then I get this error message:

my.calls <- mas5calls(my.affy)
'getOption("repos")' replaces Bioconductor standard repositories, see '?repositories'
for details

replacement repositories:
    CRAN: https://cran.rstudio.com/

Error in getCdfInfo(object) : 
    Could not obtain CDF environment, problems encountered:
 Specified environment does not contain miRNA-4_0
 Library - package mirna40cdf not installed
 Bioconductor - mirna40cdf not available

The answers I got here in the forum have unfortunately brought me nothing. I would like to use the mas5calls function.

Thanks for all answers.

R Bioconductor mas5calls • 391 views
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Please see related post: miRNA microarray analysis

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As mentioned before, this answer did not help me.

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@james-w-macdonald-5106
Last seen 1 day ago
United States

You cannot use mas5calls on a miRNA-4_0 array. There are no MM probes on that array, so it is not possible to get MAS-5.0 calls, because that requires a comparison between PM and MM probes.

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Thank you for the information. I did not know that. Would you have a tip how I could proceed differently?

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Yes. Follow the recommendation in the link that was provided to you by Lori Shepherd.

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Also: you could consider using DABG for present/absent calls. James elaborated on this in this thread: Oligo package: paCalls questions

... and combine that with his insights in this thread: Methods for removing unexpressed probes of Human Transcriptome Array HTA 2.0

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Except that the miRNA arrays are sort of dumb. An miRNA is 21-23 nt long, and Affy probes are ... 25 nt long. So a 'probeset' for an Affy miRNA array is a bunch of identical 25-mers. Plus, they tend to be super dim, so it's hard to discern which probesets are being expressed and which aren't.

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Thanks for all answers. I have tried, but still get an error message. Do you know how I can work around this?

    > library(pd.mirna.4.0)
    > library(oligo)
    > setwd("microArray/A549_ALI(1)/A549_ALI/4_tert-Butanol (22)/")
    > cel_Files <- oligoClasses::list.celfiles()
    > affyRaw <- oligo::read.celfiles(cel_Files)
    Lade nötiges Paket: pd.mirna.4.0
    Lade nötiges Paket: RSQLite
    Lade nötiges Paket: DBI
    Platform design info loaded.
    Reading in : (46) 22-B1-1_(miRNA-4_0).CEL
    Reading in : (47) 22-B1-2_(miRNA-4_0).CEL
    Reading in : (48) 22-B1-3_(miRNA-4_0).CEL
    Reading in : (49) 22-R1-1_(miRNA-4_0).CEL
    Reading in : (50) 22-NEC 1-1_(miRNA-4_0).CEL
    Reading in : (51) 22-B2-1_(miRNA-4_0).CEL
    Reading in : (52) 22-B2-2_(miRNA-4_0).CEL
    Reading in : (53) 22-B2-3_(miRNA-4_0).CEL
    Reading in : (54) 22-R2-1_(miRNA-4_0).CEL
    Reading in : (55) 22-NEC 2-1_(miRNA-4_0).CEL
    Reading in : (56) 22-B3-1_(miRNA-4_0).CEL
    Reading in : (57) 22-B3-2_(miRNA-4_0).CEL
    Reading in : (58) 22-B3-3_(miRNA-4_0).CEL
    Reading in : (59) 22-R3-1_(miRNA-4_0).CEL
    Reading in : (60) 22-NEC 3-1_(miRNA-4_0).CEL
    > paCalls_ <- paCalls(affyRaw, "PSDABG")
    Error in match.arg(method, "MAS5") : 'arg' should be “MAS5”
   > paCalls_ <- paCalls(affyRaw, "DABG")
   Error in match.arg(method, "MAS5") : 'arg' should be “MAS5”
   > paCalls_ <- paCalls(affyRaw, "MAS5")
   Getting probe level data... Error: no such table: mmfeature 
   > paCalls_2 <- oligo::paCalls(object = affyRaw)
   Getting probe level data... Error: no such table: mmfeature
   > paCalls_2 <- oligo::paCalls(object = affyRaw, "DABG")
   Error in match.arg(method, "MAS5") : 'arg' should be “MAS5”
   > paCalls_2 <- oligo::paCalls(object = affyRaw, "MAS5")
   Getting probe level data... Error: no such table: mmfeature
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The paCalls function in oligo is meant to do the MAS5.0 calls that you could have previously done using mas5calls with the affy package. As I mentioned already, you cannot compute MAS5.0 calls using an array that has no MM probes.

You will also face difficulties trying to filter out probesets on this array. These arrays are very dim, and it is difficult to distinguish between probesets that are measuring anything and those that are not. And there are not even enough on the array that filtering them out will gain you anything, so you would do better to quit trying to filter and just go forward with all the probesets.

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