[BioC] pd.hugene.2.0.st missing normgene->exon mappings
cstrato
cstrato at aon.at
Thu Jul 11 19:53:38 CEST 2013
Dear Mark,
This needs probably to be answered by Jim, since for me everything is ok
as is.
Best regards,
Christian
On 7/11/13 1:55 AM, Mark Cowley wrote:
> Hi,
> is it feasible to add a 'type' column to the core_mps table, using info from the transcript csv file? since 'core' implies transcript-level analysis.
>
> cheers,
> Mark
>
> On 11/07/2013, at 4:29 AM, cstrato <cstrato at aon.at>
> wrote:
>
>> Dear Mark,
>>
>> Yes, EIF3D and pos_controls mentioned have different transcript cluster id's. However, imho this means only that they have received these additional transcript cluster id's to be able to define them as normgene->exon. Furthermore, in the transcript annotation file the transcript_cluster_id is identical to the probeset_id. Thus e.g. 16934607 is used as probeset_id in the probeset annotation file.
>>
>> I have tested a couple of normgene->exon controls and it seems that all of them belong to real genes in the probeset csv file with the type 'main'. Mostly, these come in groups belonging to the same exon_id, e.g. the mentioned controls 16934607 - 16934610 all belong to exon_id 5192052 of the EIF3D gene.
>>
>> I suppose that you use exons as normgene->exon controls which e.g. in the case of alternative splicing are always expressed.
>>
>> Best regards,
>> Christian
>>
>>
>> On 7/10/13 12:31 PM, Mark Cowley wrote:
>>> Hi,
>>> I see the point you're making Christian.
>>> I'm offline now, so cant check this, but i assume that EIF3D and the pos_control meta-probeset in question have different transcript cluster id's. it doesn't make sense for the pos_control transcript cluster Id to be tagged as 'main'. My grep -f was still running when i left work to confirm whether all normgene->exon probesets are all deployed within different real genes in the probeset csv file.
>>>
>>> Cheers and thanks for looking into this
>>>
>>> Mark
>>>
>>> Sent from my iPhone
>>>
>>> On 10/07/2013, at 7:53 AM, "cstrato" <cstrato at aon.at> wrote:
>>>
>>>> Dear Jim,
>>>>
>>>> As far as I understand it, at the transcript level 16934607 is on one hand part of the EIF3D transcript and on the other hand does serve as a positive control. To me this seems to be no contradiction, but probably only DevNet can explain.
>>>>
>>>> Best regards,
>>>> Christian
>>>>
>>>>
>>>> On 7/9/13 11:46 PM, James W. MacDonald wrote:
>>>>> Hi Christian,
>>>>>
>>>>> Thanks for pointing that out. There is still a bit of an inconsistency
>>>>> with the pd packages that should probably be corrected, as at the
>>>>> probeset level e.g., 16934607 is intended to measure an exon of EIF3D,
>>>>> whereas at the transcript level, this same probeset is intended to be a
>>>>> positive control (and as you note below, these probes are incorporated
>>>>> into a larger probeset intended to measure the EIF3D transcript).
>>>>>
>>>>> It would be nice to be able to filter out the controls like Mark
>>>>> attempted (and I do regularly as well).
>>>>>
>>>>> Mark - I talked with Benilton Carvalho about this, and he will take a
>>>>> look next week.
>>>>>
>>>>> Best,
>>>>>
>>>>> Jim
>>>>>
>>>>>
>>>>>
>>>>> On 7/9/2013 3:38 PM, cstrato wrote:
>>>>>> Dear Jim,
>>>>>>
>>>>>> In xps I use as basic file for exon arrays the probeset annotation
>>>>>> file and then compare the data to the data from the pgf-file. Any
>>>>>> differences will be reported.
>>>>>>
>>>>>> I have just checked the different files for HuGene-2_0-st. If you
>>>>>> check as an example the following probeset_ids:
>>>>>> 16934607
>>>>>> 16934608
>>>>>> 16934609
>>>>>> 16934610
>>>>>>
>>>>>> Then you will see that the transcript annotation file lists these ids
>>>>>> as 'normgene->exon' and 'pos_control'. However, the probeset
>>>>>> annotation file lists these ids as 'main' belonging to gene EIF3D with
>>>>>> transcript_cluster_id 16934583. Looking for this id in the transcript
>>>>>> annotation file reveals that the number of 'total_probes' is 24.
>>>>>> Indeed, the probeset annotation file lists 24 probesets including the
>>>>>> four above mentioned probeset_ids.
>>>>>>
>>>>>> This means that although these four probesets are listed in the
>>>>>> transcript annotation file as 'normgene->exon' the label 'main' in the
>>>>>> pgf-file is correct since these probesets are part of the gene EIF3D.
>>>>>>
>>>>>> Interestingly, the pgf-file for HuGene-1_0-st has extra probesets
>>>>>> listed as 'normgene->exon'. However, in this case these probesets are
>>>>>> also listed as 'normgene->exon' in the probeset annotation file, i.e.
>>>>>> these probesets do not belong to any transcript listed in the probeset
>>>>>> annotation file.
>>>>>>
>>>>>> Best regards,
>>>>>> Christian
>>>>>>
>>>>>>
>>>>>> On 7/9/13 8:46 PM, James W. MacDonald wrote:
>>>>>>> Hi Christian,
>>>>>>>
>>>>>>> That's not the issue. Instead, the issue is that the pgf file lists the
>>>>>>> normgene->exon probeset IDs as being 'main'. I have received a response
>>>>>>> from Affy stating that the qcc file lists the normgene->exon probesets
>>>>>>> as pos_control, but that seems orthogonal to the issue at hand.
>>>>>>>
>>>>>>>> qcc <- read.table("HuGene-2_0-st.qcc", comment.char="#",
>>>>>>> stringsAsFactors=F, header=T)
>>>>>>>> pgf <- readPgf("HuGene-2_0-st.pgf")
>>>>>>>> head(qcc)
>>>>>>> probeset_id group_name probeset_name quantification_in_header
>>>>>>> 1 16650001 neg_control 16650001 0
>>>>>>> 2 16650003 neg_control 16650003 0
>>>>>>>
>>>>>>> ## get the positive controls (normgene->exon probesets) from the qcc
>>>>>>> file
>>>>>>>> pos_cont <- qcc[qcc[,2] == "pos_control",1]
>>>>>>>
>>>>>>> ## compare to pgf file
>>>>>>>> x <- pgf$probesetType[pgf$probesetId %in% pos_cont]
>>>>>>>> table(x)
>>>>>>> x
>>>>>>> main
>>>>>>> 1626
>>>>>>>
>>>>>>> So in the pgf file, these probesets are being called 'main' instead of
>>>>>>> some sort of control. How do you handle this in xps? Do you use the pgf
>>>>>>> file?
>>>>>>>
>>>>>>> Best,
>>>>>>>
>>>>>>> Jim
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> On 7/9/2013 2:06 PM, cstrato wrote:
>>>>>>>> Dear Jim,
>>>>>>>>
>>>>>>>> I did not really follow the discussion so I may be wrong, but if you
>>>>>>>> mean that there is a difference between the number of 'main' types,
>>>>>>>> please note that number of 'main' for pgf, i.e 349012, corresponds to
>>>>>>>> the number of 'main' in the probeset annotation file and not in the
>>>>>>>> transcript annotation file.
>>>>>>>>
>>>>>>>> But as I said, I may have misunderstood the problem.
>>>>>>>>
>>>>>>>> I am mainly replying because at the beginning of this year I had long
>>>>>>>> discussions with DevNet to make sure that the annotation files for the
>>>>>>>> 2.X arrays are correct, and in version na33.2 DevNet did correct
>>>>>>>> everything what I have found.
>>>>>>>>
>>>>>>>> Best regards,
>>>>>>>> Christian
>>>>>>>>
>>>>>>>>
>>>>>>>> On 7/9/13 7:13 PM, James W. MacDonald wrote:
>>>>>>>>> Hi Mark,
>>>>>>>>>
>>>>>>>>> Thanks for the heads-up. We already knew that Affy messed up the
>>>>>>>>> transcript and probeset annotation files (and had them fixed), but
>>>>>>>>> didn't think I needed to check the others. Famous last words, no?
>>>>>>>>>
>>>>>>>>>> x <- readPgf("HuGene-2_0-st.pgf")
>>>>>>>>>> table(x$probesetType)
>>>>>>>>>
>>>>>>>>> control->affx control->affx->bac_spike
>>>>>>>>> 18 18
>>>>>>>>> control->affx->ercc_spike control->affx->polya_spike
>>>>>>>>> 92 39
>>>>>>>>> control->bgp->antigenomic main
>>>>>>>>> 23 349012
>>>>>>>>> normgene->intron reporter
>>>>>>>>> 3575 82
>>>>>>>>>
>>>>>>>>>> y <- read.csv("HuGene-2_0-st-v1.na33.2.hg19.transcript.csv",
>>>>>>>>> comment.char = "#", stringsAsFactors=FALSE, header = TRUE)
>>>>>>>>>> table(y$category)
>>>>>>>>>
>>>>>>>>> control->affx control->affx->bac_spike
>>>>>>>>> 18 18
>>>>>>>>> control->affx->ercc-spike control->affx->polya_spike
>>>>>>>>> 92 39
>>>>>>>>> control->bgp->antigenomic main
>>>>>>>>> 23 44629
>>>>>>>>> normgene->exon normgene->intron
>>>>>>>>> 1626 3575
>>>>>>>>> reporter rescue
>>>>>>>>> 82 3515
>>>>>>>>>
>>>>>>>>> I'll ping Affymetrix and see what they have to say.
>>>>>>>>>
>>>>>>>>> Best,
>>>>>>>>>
>>>>>>>>> Jim
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> On 7/9/2013 3:29 AM, Mark Cowley wrote:
>>>>>>>>>> Dear Benilton, James& Bioconductors,
>>>>>>>>>> Thanks for providing the platform design packages for
>>>>>>>>>> hugene/mogene/ragene 1.0/1.1/2.0/2.1 arrays.
>>>>>>>>>>
>>>>>>>>>> I use SQL to query these packages& ultimately retain only 'main'
>>>>>>>>>> probes in my analysis. This works well for 1.0 and 1.1 packages, but
>>>>>>>>>> nor for 2.0 and 2.1 ST arrays. For 2.0 and 2.1 arrays, the
>>>>>>>>>> normgene->exon control probes are misclassified as 'main' probes.
>>>>>>>>>>
>>>>>>>>>> evidence: the HuGene-2_0-st-v1.na33.2.hg19.transcript.csvNetAffx csv
>>>>>>>>>> files lists 1626 normgene->exon probes, however the pg.hugene.2.0.st
>>>>>>>>>> package lists 0, and assigns these 1626 probes to the 'main'
>>>>>>>>>> category:
>>>>>>>>>>
>>>>>>>>>> # probe types:
>>>>>>>>>> library(pd.hugene.2.0.st)
>>>>>>>>>> conn<- db(pd.hugene.2.0.st)
>>>>>>>>>> dbGetQuery(conn,"SELECT * from type_dict")
>>>>>>>>>> type type_id
>>>>>>>>>> 1 1 main
>>>>>>>>>> 2 2 control->affx
>>>>>>>>>> 3 3 control->chip
>>>>>>>>>> 4 4 control->bgp->antigenomic
>>>>>>>>>> 5 5 control->bgp->genomic
>>>>>>>>>> 6 6 normgene->exon
>>>>>>>>>> 7 7 normgene->intron
>>>>>>>>>> 8 8 rescue->FLmRNA->unmapped
>>>>>>>>>> 9 9 control->affx->bac_spike
>>>>>>>>>> 10 10 oligo_spike_in
>>>>>>>>>> 11 11 r1_bac_spike_at
>>>>>>>>>>
>>>>>>>>>> # probe counts for each of the probe categories:
>>>>>>>>>> dbGetQuery(conn,"SELECT type, count(*) from featureSet GROUP BY
>>>>>>>>>> type")
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 3728
>>>>>>>>>> 2 1 345497
>>>>>>>>>> 3 2 18
>>>>>>>>>> 4 4 23
>>>>>>>>>> 5 7 3575
>>>>>>>>>> 6 9 18
>>>>>>>>>>
>>>>>>>>>> NB: no type 6 probes.
>>>>>>>>>> I've tested all 12 ho/mo/ra gene 1.0,1.1,2.0,2.1 ST packages, and see
>>>>>>>>>> this issue for all 2.0 and 2.1 arrays (see below)
>>>>>>>>>>
>>>>>>>>>> Can these mappings please be updated?
>>>>>>>>>>
>>>>>>>>>> PS, there's a bunch of probes with type = NA in the database. I
>>>>>>>>>> haven't investigated these in any detail.
>>>>>>>>>>
>>>>>>>>>> cheers,
>>>>>>>>>> Mark
>>>>>>>>>> -----------------------------------------------------
>>>>>>>>>> Mark Cowley, PhD
>>>>>>>>>>
>>>>>>>>>> Genome Informatics Division& the Centre for Clinical Genomics
>>>>>>>>>> The Kinghorn Cancer Centre, Garvan Institute of Medical Research,
>>>>>>>>>> Sydney, Australia
>>>>>>>>>> -----------------------------------------------------
>>>>>>>>>>
>>>>>>>>>> All 12 packages below:
>>>>>>>>>> pd.packages<- c(
>>>>>>>>>> "pd.hugene.1.0.st.v1", "pd.hugene.1.1.st.v1", "pd.hugene.2.0.st",
>>>>>>>>>> "pd.hugene.2.1.st",
>>>>>>>>>> "pd.mogene.1.0.st.v1", "pd.mogene.1.1.st.v1", "pd.mogene.2.0.st",
>>>>>>>>>> "pd.mogene.2.1.st",
>>>>>>>>>> "pd.ragene.1.0.st.v1", "pd.ragene.1.1.st.v1", "pd.ragene.2.0.st",
>>>>>>>>>> "pd.ragene.2.1.st"
>>>>>>>>>> )
>>>>>>>>>>
>>>>>>>>>> a<- b<- list()
>>>>>>>>>> for(pd.pkg.name in pd.packages) {
>>>>>>>>>> try({
>>>>>>>>>> require(pd.pkg.name, character.only=TRUE) || stop("Can't load
>>>>>>>>>> the
>>>>>>>>>> pd.package")
>>>>>>>>>> conn<- db(get(pd.pkg.name))
>>>>>>>>>> a[[pd.pkg.name]]<- dbGetQuery(conn,"SELECT type, count(*) from
>>>>>>>>>> featureSet GROUP BY type")
>>>>>>>>>> b[[pd.pkg.name]]<- dbGetQuery(conn,"SELECT fsetid from
>>>>>>>>>> featureSet
>>>>>>>>>> WHERE type = 6")[,1]
>>>>>>>>>> })
>>>>>>>>>> }
>>>>>>>>>> dbGetQuery(conn,"SELECT * from type_dict")
>>>>>>>>>>
>>>>>>>>>>> a
>>>>>>>>>> $pd.hugene.1.0.st.v1
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 227
>>>>>>>>>> 2 1 253002
>>>>>>>>>> 3 2 57
>>>>>>>>>> 4 4 45
>>>>>>>>>> 5 6 1195
>>>>>>>>>> 6 7 2904
>>>>>>>>>>
>>>>>>>>>> $pd.hugene.1.1.st.v1
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 227
>>>>>>>>>> 2 1 253002
>>>>>>>>>> 3 2 57
>>>>>>>>>> 4 4 45
>>>>>>>>>> 5 6 1195
>>>>>>>>>> 6 7 2904
>>>>>>>>>>
>>>>>>>>>> $pd.hugene.2.0.st
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 3728
>>>>>>>>>> 2 1 345497
>>>>>>>>>> 3 2 18
>>>>>>>>>> 4 4 23
>>>>>>>>>> 5 7 3575
>>>>>>>>>> 6 9 18
>>>>>>>>>>
>>>>>>>>>> $pd.hugene.2.1.st
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 3728
>>>>>>>>>> 2 1 345497
>>>>>>>>>> 3 2 18
>>>>>>>>>> 4 4 23
>>>>>>>>>> 5 7 3575
>>>>>>>>>> 6 9 18
>>>>>>>>>>
>>>>>>>>>> $pd.mogene.1.0.st.v1
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 86
>>>>>>>>>> 2 1 234878
>>>>>>>>>> 3 2 21
>>>>>>>>>> 4 4 45
>>>>>>>>>> 5 6 1324
>>>>>>>>>> 6 7 5222
>>>>>>>>>>
>>>>>>>>>> $pd.mogene.1.1.st.v1
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 86
>>>>>>>>>> 2 1 234878
>>>>>>>>>> 3 2 21
>>>>>>>>>> 4 4 45
>>>>>>>>>> 5 6 1324
>>>>>>>>>> 6 7 5222
>>>>>>>>>>
>>>>>>>>>> $pd.mogene.2.0.st
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 810
>>>>>>>>>> 2 1 263551
>>>>>>>>>> 3 2 18
>>>>>>>>>> 4 4 23
>>>>>>>>>> 5 7 5331
>>>>>>>>>> 6 9 18
>>>>>>>>>>
>>>>>>>>>> $pd.mogene.2.1.st
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 810
>>>>>>>>>> 2 1 263551
>>>>>>>>>> 3 2 18
>>>>>>>>>> 4 4 23
>>>>>>>>>> 5 7 5331
>>>>>>>>>> 6 9 18
>>>>>>>>>>
>>>>>>>>>> $pd.ragene.1.0.st.v1
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 254
>>>>>>>>>> 2 1 211195
>>>>>>>>>> 3 2 21
>>>>>>>>>> 4 4 45
>>>>>>>>>> 5 6 399
>>>>>>>>>> 6 7 1153
>>>>>>>>>>
>>>>>>>>>> $pd.ragene.1.1.st.v1
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 254
>>>>>>>>>> 2 1 211195
>>>>>>>>>> 3 2 21
>>>>>>>>>> 4 4 45
>>>>>>>>>> 5 6 399
>>>>>>>>>> 6 7 1153
>>>>>>>>>>
>>>>>>>>>> $pd.ragene.2.0.st
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 1071
>>>>>>>>>> 2 1 214018
>>>>>>>>>> 3 2 18
>>>>>>>>>> 4 4 23
>>>>>>>>>> 5 7 5083
>>>>>>>>>> 6 9 18
>>>>>>>>>>
>>>>>>>>>> $pd.ragene.2.1.st
>>>>>>>>>> type count(*)
>>>>>>>>>> 1 NA 1071
>>>>>>>>>> 2 1 214018
>>>>>>>>>> 3 2 18
>>>>>>>>>> 4 4 23
>>>>>>>>>> 5 7 5083
>>>>>>>>>> 6 9 18
>>>>>>>>>>
>>>>>>>>>>> sapply(b,length)
>>>>>>>>>> pd.hugene.1.0.st.v1 pd.hugene.1.1.st.v1 pd.hugene.2.0.st
>>>>>>>>>> pd.hugene.2.1.st
>>>>>>>>>> 1195 1195
>>>>>>>>>> 0 0
>>>>>>>>>> pd.mogene.1.0.st.v1 pd.mogene.1.1.st.v1 pd.mogene.2.0.st
>>>>>>>>>> pd.mogene.2.1.st
>>>>>>>>>> 1324 1324
>>>>>>>>>> 0 0
>>>>>>>>>> pd.ragene.1.0.st.v1 pd.ragene.1.1.st.v1 pd.ragene.2.0.st
>>>>>>>>>> pd.ragene.2.1.st
>>>>>>>>>> 399 399
>>>>>>>>>> 0 0
>>>>>>>>>>
>>>>>>>>>>> sessionInfo()
>>>>>>>>>> R version 3.0.0 (2013-04-03)
>>>>>>>>>> Platform: x86_64-unknown-linux-gnu (64-bit)
>>>>>>>>>>
>>>>>>>>>> locale:
>>>>>>>>>> [1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C
>>>>>>>>>> [3] LC_TIME=en_AU.UTF-8 LC_COLLATE=en_AU.UTF-8
>>>>>>>>>> [5] LC_MONETARY=en_AU.UTF-8 LC_MESSAGES=en_AU.UTF-8
>>>>>>>>>> [7] LC_PAPER=C LC_NAME=C
>>>>>>>>>> [9] LC_ADDRESS=C LC_TELEPHONE=C
>>>>>>>>>> [11] LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C
>>>>>>>>>>
>>>>>>>>>> attached base packages:
>>>>>>>>>> [1] parallel stats graphics grDevices utils datasets
>>>>>>>>>> methods
>>>>>>>>>> [8] base
>>>>>>>>>>
>>>>>>>>>> other attached packages:
>>>>>>>>>> [1] pd.ragene.2.1.st_2.12.1 pd.ragene.2.0.st_2.12.0
>>>>>>>>>> [3] pd.ragene.1.1.st.v1_3.8.0 pd.ragene.1.0.st.v1_3.8.0
>>>>>>>>>> [5] pd.mogene.2.1.st_2.12.1 pd.mogene.2.0.st_2.12.0
>>>>>>>>>> [7] pd.mogene.1.1.st.v1_3.8.0 pd.mogene.1.0.st.v1_3.8.0
>>>>>>>>>> [9] pd.hugene.2.1.st_3.8.0 pd.hugene.1.1.st.v1_3.8.0
>>>>>>>>>> [11] pd.hugene.1.0.st.v1_3.8.0 pd.hugene.2.0.st_3.8.0
>>>>>>>>>> [13] oligo_1.24.0 Biobase_2.20.0
>>>>>>>>>> [15] oligoClasses_1.22.0 BiocGenerics_0.6.0
>>>>>>>>>> [17] RSQLite_0.11.4 DBI_0.2-7
>>>>>>>>>> [19] BiocInstaller_1.10.2
>>>>>>>>>>
>>>>>>>>>> loaded via a namespace (and not attached):
>>>>>>>>>> [1] affxparser_1.32.1 affyio_1.28.0 Biostrings_2.28.0
>>>>>>>>>> [4] bit_1.1-10 codetools_0.2-8 ff_2.2-11
>>>>>>>>>> [7] foreach_1.4.1 GenomicRanges_1.12.3 IRanges_1.18.1
>>>>>>>>>> [10] iterators_1.0.6 preprocessCore_1.22.0 splines_3.0.0
>>>>>>>>>> [13] stats4_3.0.0 tools_3.0.0 zlibbioc_1.6.0
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> [[alternative HTML version deleted]]
>>>>>>>>>>
>>>>>>>>>> _______________________________________________
>>>>>>>>>> Bioconductor mailing list
>>>>>>>>>> Bioconductor at r-project.org
>>>>>>>>>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>>>>>>>>>> Search the archives:
>>>>>>>>>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>>>>>
>>>
>
>
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