Hello
I am trying to use biomaRt for what seems to be a simple query.
I have a list of transcript IDs from affymetrix Rat Exon arrays.
I would like to get some associated identifiers such as the entrez
gene id or th gene symbol.
I have done the following
######################
library("biomaRt")
### Seleccio de la base de dades i el 'dataset' (aquest darrer ve
definit per l'organisme)
ensemblMart<- useMart("ensembl")
# listDatasets (ensemblMart) # omitted in the message
ensemblMart <- useMart("ensembl", dataset="rnorvegicus_gene_ensembl")
# ratFilters<-listFilters(ensemblMart) # omitted in the message
filters1 <- "affy_raex_1_0_st_v1"
transcriptIDs1 <- c("7241279","7332324","7241281","7199205","7112511")
# listAttributes(ensemblMart) # omitted in the message
attributes1 <-c("affy_raex_1_0_st_v1","entrezgene","rgd_symbol")
getBM(attributes = attributes1,
filters=filters1,
values=transcriptIDs1,
mart=ensemblMart)
#######################
but I obtain an empty result
[1] affy_raex_1_0_st_v1 entrezgene rgd_symbol
<0 rows> (or 0-length row.names)
#######################
I have used R 2.9 in Ubuntu and windows and I have obtained the same
results.
I presume I must be doing something wrong because these IDs do have
entrez gene and symbol IDs
(Verified in NetAffy)
Any help will be appreciated.
Thanks
Alex Sánchez
----------------------------------------------------------------------
-------------------------------
Dr. Alex Sánchez. Statistics Department. University of Barcelona.
Facultat de Biologia UB. Avda Diagonal 645. 08028 Barcelona. Spain
asanchez_at_ub.edu
Statistics and Bioinformatics Unit
Institut de Recerca. Hospital Universitari Vall 'Hebron
Passeig Vall d'Hebron 112-119. 08034 Barcelona
asanchez_at_ir.vhebron.net
----------------------------------------------------------------------
------------------------------
[[alternative HTML version deleted]]
Hello Alex,
The trick is that your IDs in the biomaRt filter are neither
transcripts nor compatible with "affy_raex_1_0_st_v1".
Your IDs are Affy transcript clusters - a bit old way of defining
features on the Affy Exon chips, abandoned as
far as I know in most of the software, perhaps except GeneSpring 10
and NetAffx.
One transcript cluster consists of several probesets, eg your first
transcript cluster has 5 probesets (check with NetAffx).
Then - those probeset IDs are compatible with your
"affy_raex_1_0_st_v1" filter and will give you results.
Btw, the job of translating rat exon probesets into genes and
transcripts is done most quickly with exonmap,
assuming that you install a local copy of X:MAP database...
Saludos!
Michal
-----Original Message-----
From: bioconductor-bounces@stat.math.ethz.ch on behalf of Alex Sanchez
Sent: Wed 11/4/2009 11:29 PM
To: bioconductor at stat.math.ethz.ch
Cc: jlmosquera at ir.vhebron.net; M. Carme Ruiz de Villa
Subject: [BioC] how to do it with biomaRt
Hello
I am trying to use biomaRt for what seems to be a simple query.
I have a list of transcript IDs from affymetrix Rat Exon arrays.
I would like to get some associated identifiers such as the entrez
gene id or th gene symbol.
I have done the following
######################
library("biomaRt")
### Seleccio de la base de dades i el 'dataset' (aquest darrer ve
definit per l'organisme)
ensemblMart<- useMart("ensembl")
# listDatasets (ensemblMart) # omitted in the message
ensemblMart <- useMart("ensembl", dataset="rnorvegicus_gene_ensembl")
# ratFilters<-listFilters(ensemblMart) # omitted in the message
filters1 <- "affy_raex_1_0_st_v1"
transcriptIDs1 <- c("7241279","7332324","7241281","7199205","7112511")
# listAttributes(ensemblMart) # omitted in the message
attributes1 <-c("affy_raex_1_0_st_v1","entrezgene","rgd_symbol")
getBM(attributes = attributes1,
filters=filters1,
values=transcriptIDs1,
mart=ensemblMart)
#######################
but I obtain an empty result
[1] affy_raex_1_0_st_v1 entrezgene rgd_symbol
<0 rows> (or 0-length row.names)
#######################
I have used R 2.9 in Ubuntu and windows and I have obtained the same
results.
I presume I must be doing something wrong because these IDs do have
entrez gene and symbol IDs
(Verified in NetAffy)
Any help will be appreciated.
Thanks
Alex S?nchez
----------------------------------------------------------------------
-------------------------------
Dr. Alex S?nchez. Statistics Department. University of Barcelona.
Facultat de Biologia UB. Avda Diagonal 645. 08028 Barcelona. Spain
asanchez_at_ub.edu
Statistics and Bioinformatics Unit
Institut de Recerca. Hospital Universitari Vall 'Hebron
Passeig Vall d'Hebron 112-119. 08034 Barcelona
asanchez_at_ir.vhebron.net
----------------------------------------------------------------------
------------------------------
[[alternative HTML version deleted]]
Hello Michal
> The trick is that your IDs in the biomaRt filter are neither
transcripts
> nor compatible with "affy_raex_1_0_st_v1".
It explains the empty return
> Your IDs are Affy transcript clusters - a bit old way of defining
features
> on the Affy Exon chips, abandoned as
> far as I know in most of the software, perhaps except GeneSpring 10
and
> NetAffx.
It is also used by the "fastuos" Partek Genomics Suite.
> One transcript cluster consists of several probesets, eg your first
> transcript cluster has 5 probesets (check with NetAffx).
> Then - those probeset IDs are compatible with your
"affy_raex_1_0_st_v1"
> filter and will give you results.
> Btw, the job of translating rat exon probesets into genes and
transcripts
> is done most quickly with exonmap,
> assuming that you install a local copy of X:MAP database...
The point is that, what we often do, is to use Gene Array or Exon
chips to
study gene expression -not alternative splicing- so what I am looking
for is
a flexible way to get the annotations for these chips a the transcript
cluster level.
Thanks for the help
Alex
----- Original Message -----
From: "Michal Okoniewski" <michal.okoniewski@fgcz.ethz.ch>
To: "Alex Sanchez" <asanchez at="" ub.edu="">; <bioconductor at="" stat.math.ethz.ch="">
Cc: <jlmosquera at="" ir.vhebron.net="">; "M. Carme Ruiz de Villa"
<mruiz_de_villa at="" ub.edu="">
Sent: Thursday, November 05, 2009 7:04 AM
Subject: RE: [BioC] how to do it with biomaRt
Hello Alex,
The trick is that your IDs in the biomaRt filter are neither
transcripts nor
compatible with "affy_raex_1_0_st_v1".
Your IDs are Affy transcript clusters - a bit old way of defining
features
on the Affy Exon chips, abandoned as
far as I know in most of the software, perhaps except GeneSpring 10
and
NetAffx.
One transcript cluster consists of several probesets, eg your first
transcript cluster has 5 probesets (check with NetAffx).
Then - those probeset IDs are compatible with your
"affy_raex_1_0_st_v1"
filter and will give you results.
Btw, the job of translating rat exon probesets into genes and
transcripts is
done most quickly with exonmap,
assuming that you install a local copy of X:MAP database...
Saludos!
Michal
-----Original Message-----
From: bioconductor-bounces@stat.math.ethz.ch on behalf of Alex Sanchez
Sent: Wed 11/4/2009 11:29 PM
To: bioconductor at stat.math.ethz.ch
Cc: jlmosquera at ir.vhebron.net; M. Carme Ruiz de Villa
Subject: [BioC] how to do it with biomaRt
Hello
I am trying to use biomaRt for what seems to be a simple query.
I have a list of transcript IDs from affymetrix Rat Exon arrays.
I would like to get some associated identifiers such as the entrez
gene id
or th gene symbol.
I have done the following
######################
library("biomaRt")
### Seleccio de la base de dades i el 'dataset' (aquest darrer ve
definit
per l'organisme)
ensemblMart<- useMart("ensembl")
# listDatasets (ensemblMart) # omitted in the message
ensemblMart <- useMart("ensembl", dataset="rnorvegicus_gene_ensembl")
# ratFilters<-listFilters(ensemblMart) # omitted in the message
filters1 <- "affy_raex_1_0_st_v1"
transcriptIDs1 <- c("7241279","7332324","7241281","7199205","7112511")
# listAttributes(ensemblMart) # omitted in the message
attributes1 <-c("affy_raex_1_0_st_v1","entrezgene","rgd_symbol")
getBM(attributes = attributes1,
filters=filters1,
values=transcriptIDs1,
mart=ensemblMart)
#######################
but I obtain an empty result
[1] affy_raex_1_0_st_v1 entrezgene rgd_symbol
<0 rows> (or 0-length row.names)
#######################
I have used R 2.9 in Ubuntu and windows and I have obtained the same
results.
I presume I must be doing something wrong because these IDs do have
entrez
gene and symbol IDs
(Verified in NetAffy)
Any help will be appreciated.
Thanks
Alex S?nchez
----------------------------------------------------------------------
-------------------------------
Dr. Alex S?nchez. Statistics Department. University of Barcelona.
Facultat de Biologia UB. Avda Diagonal 645. 08028 Barcelona. Spain
asanchez_at_ub.edu
Statistics and Bioinformatics Unit
Institut de Recerca. Hospital Universitari Vall 'Hebron
Passeig Vall d'Hebron 112-119. 08034 Barcelona
asanchez_at_ir.vhebron.net
----------------------------------------------------------------------
------------------------------
[[alternative HTML version deleted]]
>
>> Btw, the job of translating rat exon probesets into genes and
>> transcripts is done most quickly with exonmap,
>> assuming that you install a local copy of X:MAP database...
>
> The point is that, what we often do, is to use Gene Array or Exon
> chips to study gene expression -not alternative splicing- so what I
am
> looking for is a flexible way to get the annotations for these chips
a
> the transcript cluster level.
>
> Thanks for the help
>
> Alex
>
>
Then - as an approximation I use Brainarray CDFs for the Entrez or
Ensembl gene level - however it comes at a price of loosing
many genes as false negatives (same for transcript clusters, I
suppose).
Brainarray is updated quite often, so should be more precise
than transcript clusters, I suppose.
In the more precise version - get all the significant
probesets in the full set (1M for rat ) and check with exonmap to
which
gene they belong.
If there are several exons having the same direction and roughly
similar
magnitude of fold change - then such a gene is OK differentially
expressed,
although you might have missed it with Brainarray mapping or
transcript
cluster approach in Partek .
Cheers,
Michal