Help with the beadarray package
1
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noa.gilat • 0
@dffeb649
Last seen 5 weeks ago
Israel

Hello,

I am using Bioconductor version 3.13 (BiocManager 1.30.16), R 4.1.1 (2021-08-10). I am handling a list of files received from Iscan machine, and I try to obtain the intensity of each bead, to my understanding the function "readIllumina" of the "beadarray" package has the option to do so. However, I am struggling to understand the correct workflow, I have ~390 output files received from the Iscan (I attached the list of file names below), and I can't seem to get the "readIllumina" to work with them. Any suggestions would be appreciated.

Many thanks,

Noa

file names (only the first 30):

[1] "205062750052.sdf"
[2] "205062750052_qc.txt"
[3] "205062750052_R01C01_1-Swath1_Grn.locs"
[4] "205062750052_R01C01_1-Swath1_Grn.tif"
[5] "205062750052_R01C01_1-Swath1_Red.locs"
[6] "205062750052_R01C01_1-Swath1_Red.tif"
[7] "205062750052_R01C01_1_beadTypeFile.txt"
[8] "205062750052_R01C01_1_Focus_scan#1_swath#1_point#1_try#1.tif" [9] "205062750052_R01C01_1_Green.xml"
[10] "205062750052_R01C01_1_perBeadFile.txt"
[11] "205062750052_R01C01_1_Red.xml"
[12] "205062750052_R01C01_2-Swath1_Grn.locs"
[13] "205062750052_R01C01_2-Swath1_Grn.tif"
[14] "205062750052_R01C01_2-Swath1_Red.locs"
[15] "205062750052_R01C01_2-Swath1_Red.tif"
[16] "205062750052_R01C01_2_beadTypeFile.txt"
[17] "205062750052_R01C01_2_Focus_scan#1_swath#1_point#1_try#1.tif" [18] "205062750052_R01C01_2_Green.xml"
[19] "205062750052_R01C01_2_perBeadFile.txt"
[20] "205062750052_R01C01_2_Red.xml"
[21] "205062750052_R01C01_3-Swath1_Grn.locs"
[22] "205062750052_R01C01_3-Swath1_Grn.tif"
[23] "205062750052_R01C01_3-Swath1_Red.locs"
[24] "205062750052_R01C01_3-Swath1_Red.tif"
[25] "205062750052_R01C01_3_beadTypeFile.txt"
[26] "205062750052_R01C01_3_Focus_scan#1_swath#1_point#1_try#1.tif" [27] "205062750052_R01C01_3_Green.xml"
[28] "205062750052_R01C01_3_perBeadFile.txt"
[29] "205062750052_R01C01_3_Red.xml"
[30] "205062750052_R01C01_4-Swath1_Grn.locs"

[388] "Effective.cfg"
[389] "Metrics.txt"

IlluminaChip beadarray • 148 views
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Do the output files include an idat file for each sample? They are the definitive files to read, although they will give probewise expression values rather than beadwise.

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Hi Gordon,

Thank you for your input. Yes for each of the 8 arrays I have two idat files- for the green ad for the red channels. I found a new and seems to be usful package in R- illuminaio, which seems to be able to do what I need. So far, I was able to receive a list of mean intensities and sd per a single array (red/green channel- depends on the IDAT file I use), by using the "readIDAT" command, and the "quants" entry"

        Mean SD NBeads
1600101   69 19     13
1600111   65 15      8
1600115   74 17     18
1600123   55 13     13
1600131   63 13     15
1600135   64 11     10

I also found another function- "readBPM" which, to my understanding, provides details of probe sequences, intended genomic targets and whether it is a control probe or not, information that is necessary to correctly interpret the data. So, do you happen to know of a way to use the information stored in this BPM file, to decifer the IDAT files, and receive a mean intensity associated to a specific targetID/sequenec ? Thanks a lot!

Noa

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@gordon-smyth
Last seen 8 hours ago
WEHI, Melbourne, Australia

Assuming that your ultimate aim is to do a gene expression analysis, the best way to process Ilumina beadarrays is via the idat files:

library(limma)
idatfiles <- dir(pattern="idat")
bgxfile <- dir(pattern="bgx")
x <- read.idat(idatfiles, bgxfile)
x$other$Detection <- detectionPValues(x)
y <- neqc(x)

The above code identifies and processes the control probes, uses them for normalization and background correction, and then removes them. The code also extracts probe annotation from the manifest file.

Background correction and normalization is done using the method described by:

Shi W, Oshlack A and Smyth GK (2010). Optimizing the noise versus bias trade-off for Illumina Whole Genome Expression BeadChips. Nucleic Acids Research 38, e204. http://nar.oxfordjournals.org/content/38/22/e204

Now you have normalized and background-corrected log-expression values ready for differential expression analysis in limma.

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