I am using two gene expression datasets from an Affy U95Av2 platform and an Affy U133 Plus 2.0 platform. When I map the Affy probe names to HUGO gene names, there are thousands of genes which exist in the newer Affy U133 Plus 2.0 dataset while not in the old Affy U95Av2 dataset, which is something expected. But there are also 97 genes which exist in the old Affy U95Av2 platform while not in Affy U133 Plus 2.0 platform. I would not expect that because Affy U133 Plus 2.0 is a much newer platform and I would expect it to contain all genes that were measured by Affy U95Av2. What does that mean? Should I understand that those 97 gene measurements in the Affy U95Av2 platform were not reliable and that's why they don't exist in Affy U133 Plus 2.0? Here are those 97 genes:

"ACSL4" "ACSM2A" "AP3S1" "AQP7" "ARPC3" "ATF4" "ATP5H" "BAK1" "BAK1P1" "CBX1" "CCL15" "CELP" "CFHR3" "CHEK2" "CLCNKA" "COL8A1" "CS" "CXorf40B" "CYP2D6" "DDI2" "EIF3F" "EIF3IP1" "EIF5AL1" "FCGR2A" "FCGR3A" "GBX1" "GPX1" "HAVCR1" "HBZ" "HIST1H2AH" "HIST1H2AI" "HIST1H2BC" "HIST1H2BJ" "HIST1H4I" "HOXA9" "HSPB1" "IFNA14" "IGF2" "IL9R" "ITGA1" "KAT7" "KRT33A" "KRTAP26-1" "LDHA" "MAGEA12" "MAP2K4P1" "MIA" "MKRN3" "MROH7" "MSX2P1" "MT1A" "MT1B" "NDUFV2" "OPHN1" "OR7E24" "PARP4" "PCDHA12" "PCDHA13" "PCDHGA12" "PCDHGB4" "PINK1-AS" "PMS2P3" "PSMC6" "PSME2" "RAB13" "RCN1" "RNF216P1" "RNF5" "RPL10A" "RPL18" "RPL27" "RPL35" "RPL37" "RPLP1" "RPS15A" "RPS26" "RPS29" "RPS5" "RPS9" "RSC1A1" "S100A7" "SAA1" "SAA4" "SNX29" "SPRR2D" "TOMM40" "UBC" "UBE2E3" "UBE2S" "UGT2B7" "UQCRFS1" "UQCRH" "VDAC2" "VENTXP7" "VOPP1" "XCL2" "ZNF799"

  • $\begingroup$ What annotation source are you using to map Affymetrix identifiers to gene names, NetAffx or ? If the annotation files are from different sources and / or generated at different times, then gene symbols may have changed in between and therefore fail to match. But in your list I clearly see well established gene symbols that have not changed for a long time, so something looks funky ... $\endgroup$ – Roland Apr 19 '16 at 19:38
  • $\begingroup$ I am using biomaRt (the same ensemble version) for mapping both. Here is my code: ensemble = useMart(host='dec2014.archive.ensembl.org', biomart='ENSEMBL_MART_ENSEMBL'); hsp = useDataset(mart=ensemble, dataset='hsapiens_gene_ensembl'); ids = getBM(filters='entrezgene', attributes=c('entrezgene','hgnc_symbol'), values=entrezgeneids, mart=hsp); $\endgroup$ – user5054 Apr 19 '16 at 19:56
  • $\begingroup$ Well, I don't know where biomart in turn gets its information. I would recommend you track down the actual annotation source, or map identifiers via a trusted source like Affy's own annotations. I just did a quick query on NetAffx for ACSL4 (first in your list) and there are definitely probes targeting this gene on the U133. It's impossible to say why the results differ without knowing exactly how the annotations were done. $\endgroup$ – Roland Apr 19 '16 at 19:58

aI used to work at Affymetrix when most of these arrays were designed. I was not on the design team itself, but I can maybe talk about this a bit more.

RNA Array designs were built to cover anything that might possibly be real transcript in the mix of EST collections, cDNA, in silico gene detections and miscellaneous entries in public databases. There were a lot of different people trying to find genes as quickly as possible and a good deal of it was not real gene naturally. I'm sure there was a reasonable amount of contamination in the millions of transcripts we took in as well.

The team would find a good number of errors in the sequence database. There is no way to submit this in a meaningful way to most bioinformatics databases by the way. Just a note:)

When a new design came out the team would do auditing to see if any of the transcripts had fallen out of favor with the evidence and some of those 'genes' would be pared from the content.

This is useful because DNA hybridization tech is very high throughput for the dollar but it has a background noise and even a probeset with no correspondence in the RNA sample will give numbers that are non-zero.

RNAseq has similar issues from assemblies and sensitivity from limits of reads on the sample BTW. There's no perfect solution as of yet.

BTW sometimes genes get renamed. I didn't get into your methods to see if this is a case, but something to keep in mind.


My experience is with Affymetrix probes for Drosophila, not H.sapiens, and only with one version. Nevertheless I'll describe the situation I encountered in case it is relevant to yours. Apologies if it is a red herring.

What I did with the Affymetrix data sheet was use it to construct my own SQL relational database containing probesetIDs and geneIDs (as well as the experimental data, of course). I was then able to make some ‘housekeeping’ queries to the database and was surprised (perhaps I shouldn’t have been) to find the following:

  • Some genes were picked up by more than one probeset. No great worry. Just had to choose the probeset that gave the highest signal, unless it fell into the second category.
  • Some probesets picked up more than one gene. This was a problem, and meant I had to classify the probesets as ambiguous or unambiguous. But an even greater problem was that for some genes there existed no unambigous probesets.

Obviously in designing the probesets Affymetrix thought they were producing unambigous gene-specific ones. When they updated the probesets to include new or corrected gene designations one imagines they would try to deal with this problem (assuming it also existed in the human gene sets). It seems hard to believe, but could the genes you mention be refractory to the preparation of unambigous probesets?

  • $\begingroup$ Thanks for the reply. I think what you explained is quite possible, and I think there are also two reasons: 1) (Thanks to mastal11 on Biostars) There are many Affy probe sets that are not all that reliable because they are based on ESTs. Also, the older arrays would have been based on older versions of the human genome sequence, and possibly some of the probesets on the older arrays don't map or don't map uniquely to the newer versions of the human genome sequence. Occasionally also, probe sets were based on GenBank sequences that were later withdrawn from GenBank. (cont. in the next comment) $\endgroup$ – user5054 Apr 23 '16 at 8:01
  • $\begingroup$ 2) Some of those 97 genes actually have mapping probes in the newer Affy platform, but the annotation source I am using to map the Affy probe sets to HUGO gene symbols, biomaRt, does not have the identifiers of those probes in its database, so cannot map them to the gene symbols. There are various annotation sources out there, and you may end up with a slightly different mapping depending on which you use. $\endgroup$ – user5054 Apr 23 '16 at 8:02

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