Hi Valerie,
Thanks a lot..It worked finally.. So now I have a data frame for the geneIds
,TranscriptIds and the counts (3'utr) which is given below:
GENE TX countsUTRctl[1,] "148398" "1121" "2" [2,] "339451"
"1118" "0" [3,] "84069" "1116" "0" [4,] "84069" "1119" "11"
[5,] "9636" "1126" "11" [6,] "375790" "1127" "0"
Now I want to do differential expression of genes using DESeq,so do I have to
merge the two same genes and its counts such as geneID 84069 (from above ) or i
can proceed with the above dataframe?If I have to merge them how do I do that?
Thanks,Rohan
--- On Sat, 24/9/11, Valerie Obenchain <voben...@fhcrc.org> wrote:
From: Valerie Obenchain <voben...@fhcrc.org>
Subject: Re: [Bioc-sig-seq] Reads in 3'utr
To: "rohan bareja" <rohan_1...@yahoo.co.in>
Cc: bioc-sig-sequencing@r-project.org
Date: Saturday, 24 September, 2011, 4:24 AM
On 09/23/2011 02:57 PM, rohan bareja wrote:
Hi,
utr=threeUTRsByTranscript(txdb,use.names=FALSE)
So,utr
is GRangesList of length 33381
Then
as u said,I did the following:
txBygene <- transcriptsBy(txdb, "gene")
geneID <- rep(names(txBygene),
elementLengths(txBygene))
df <- data.frame(geneID=geneID,
txID=values(unlist(txBygene))[["tx_id"]])
This
gives me a dataframe with 40,780 rows with gene ID and
txID from txBygene object.
geneID txID
40775 9994 11731
40776 9994 11730
40777 9997 38491
40778 9997 38489
40779 9997 38496
40780 9997 38497
Since my utr object is of length 33,381 ,my
counts length is same i.e 33,381
So I am not able to map the counts to the above
data frame which has transcript and gene IDs.
Yes, these lengths are different.
In this example we have utr regions from 58 transcripts.
> length(utr)
[1] 58
Those 58 transcripts can be matched to their gene ID's by looking at
the txBygene object. All of the transcripts fall into one (or more)
of 51 genes,
> length(txBygene)
[1] 51
There are multiple transcripts per gene so we expand the gene ID's
to map to the transcripts.
> dim(df)
[1] 79 2
This data.frame has all transcripts from the txdb mapped to the gene
ID's. Your utr data may contain only a subset of these transcripts.
That is something you need to check. Match the desired transcript
names to the df, pull out the gene IDs. You then have the gene ID's
for your utr regions and can split or group your counts by gene.
Valerie
---
On Fri, 23/9/11, Valerie Obenchain <voben...@fhcrc.org> wrote:
From: Valerie Obenchain <voben...@fhcrc.org>
Subject: Re: [Bioc-sig-seq] Reads in 3'utr
To: "rohan bareja" <rohan_1...@yahoo.co.in>
Cc: bioc-sig-sequencing@r-project.org
Date: Friday, 23 September, 2011, 10:50 PM
Hi Rohan,
You can relate the counts for 3UTR regions to gene
IDs through the transcript IDs.
txdb_file <- system.file("extdata",
"UCSC_knownGene_sample.sqlite",
package="GenomicFeatures")
txdb <- loadFeatures(txdb_file)
utr=threeUTRsByTranscript(txdb,use.names=FALSE)
The transcript names can be matched to the gene ID's
through,
txBygene <- transcriptsBy(txdb, "gene")
geneID <- rep(names(txBygene),
elementLengths(txBygene))
df <- data.frame(geneID=geneID,
txID=values(unlist(txBygene))[["tx_id"]])
Now you know what gene ID each tx count belongs to.
You can split your counts by gene ID ...
Valerie
On 09/20/2011 12:13 PM, rohan bareja wrote:
Hi everyone,
I am doing NGS analysis using bam files.I have counted reads in 3'utr region
using
utr=threeUTRsByTranscript(txdb,use.names=FALSE)
countsUTR <- countOverlaps(utr,reads)
I have got the transcript level counts from this.How can I get the gene level
counts??It might sound silly but Does anybody have an idea on what type of
anaylses we can do from this countsUTR ?
Thanks,Rohan
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