Entering edit mode
Dear Kaur,
The XS:A tag does not tell you the strand to which the read was
mapped. It tells you the strand where the exon splicing occurs. The
aligner uses the donor/receptor bases (GT/AG) to determine the strand
where the splicing happens.
The strand which a read is mapped to is reported in the FLAG field in
a SAM/BAM file and that is the information featureCounts uses to
perform strand specific read summarization. I would suggest you to
have a close look at your read mapping results using a genome browser
like IGB so that you can have a better understanding of strandness of
your reads and annotated genes.
Best regards,
Wei
On Aug 30, 2014, at 12:44 AM, Kaur Alasoo wrote:
> Dear Wei,
>
> Thanks for your quick reply. I think the problem might be how the
strand is represented in the BAM file. I used Tophat2 to perform the
alignment and it uses XS:A:+ or XS:A:- tags to specify whether the
read comes from the forward or the reverse strand, respectively. When
I split the reads by chromosome and then count how many of them map to
each strand I get the what is expected in the annotations:
>
> On chromosome 11 almost all reads are on reverse strand.
ENSG00000066336 is also on on the reverse strand.
> $ samtools view merged.bam | awk '{if ($3 == "11") {print $0}}' |
grep "XS:A:-" | wc -l
> 23410
> $ samtools view merged.bam | awk '{if ($3 == "11") {print $0}}' |
grep "XS:A:+" | wc -l
> 5
>
> On chromosome 9 almost all read are on the forward strand.
ENSG00000136869 is also on the fwd strand.
> $ samtools view merged.bam | awk '{if ($3 == "9") {print $0}}' |
grep "XS:A:-" | wc -l
> 80
> $ samtools view merged.bam | awk '{if ($3 == "9") {print $0}}' |
grep "XS:A:+" | wc -l
> 8628
>
> Which field of the BAM files does featureCounts use to infer the
strand of the read?
>
> Best wishes,
> Kaur
>
>
> On 29 Aug 2014, at 03:59, Wei Shi <shi at="" wehi.edu.au=""> wrote:
>
>> Dear Kaur,
>>
>> We had a close look at the reads in your supplied bam file and
found that most of the reads were mapped to the positive strand. This
is inconsistent with the annotation for the two genes you listed, ie.
the read mapping results tell you that both genes are on the positive
strand but the annotation data tell you that the two genes are on
different strands.
>>
>> When strandSpecific is set to 1, featureCounts requires the strand
of a read is the same as that of a gene before assigning the read to
the gene. When strandSpecific is set to 2, featureCounts will flip the
strand of each read and then try to match it to the strands of genes.
Since your two genes are on different strands but the reads are almost
all on the same strand, you will never get large counts (or small
counts) for the two genes at the same time.
>>
>> This is not a problem of featureCounts. featureCounts just assigns
the reads using the strand info provided in the mapping results. This
is more like a problem with either the annotation or read mapping or
maybe the sequencing experiment.
>>
>> Hope this helps.
>>
>> Best wishes,
>>
>> Wei
>>
>>
>>
>> On Aug 28, 2014, at 12:53 AM, Kaur Alasoo [guest] wrote:
>>
>>> Hi,
>>>
>>> I am trying to use featureCounts to perform strand-specifc RNA-Seq
read counting with an Ensembl GTF file. However, it seems to count
reads from each strand separately rather than for each gene from the
strand where the gene is located. I have created a small BAM that
contains reads from only two genes (one from each strand) to
illustrate the problem.
>>>
>>> First, if I specify strandSpefic = 0 I get 97.7% of the reads
aligned to two genes:
>>> a = featureCounts("merged.bam", annot.ext =
"Homo_sapiens.GRCh38.76.gtf",
>>> strandSpecific = 0, isGTFAnnotationFile = TRUE, isPairedEnd =
TRUE)
>>>
>>>> a$stat
>>> Status counts.merged.bam
>>> 1 Assigned 16179
>>> 2 Unassigned_Ambiguity 0
>>> 3 Unassigned_MultiMapping 56
>>> 4 Unassigned_NoFeatures 335
>>>
>>> And the reads counts for the two genes are:
>>>> a$counts[c("ENSG00000066336","ENSG00000136869"),]
>>> ENSG00000066336 ENSG00000136869
>>> 11759 4419
>>>
>>> However, when I try to specifiy strandSpecific = 1 or 2 I get
reads from only one strand counted in either case
>>> b = featureCounts("counts/merged.bam", annot.ext =
"../../annotations/GRCh38/genes/Homo_sapiens.GRCh38.76.gtf",
strandSpecific = 1, isGTFAnnotationFile = TRUE, isPairedEnd = TRUE)
>>>
>>>> b$stat
>>> Status counts.merged.bam
>>> 1 Assigned 5295
>>> 2 Unassigned_Ambiguity 0
>>> 3 Unassigned_MultiMapping 56
>>> 4 Unassigned_NoFeatures 11219
>>>
>>>> b$counts[c("ENSG00000066336","ENSG00000136869"),]
>>> ENSG00000066336 ENSG00000136869
>>> 952 4343
>>>
>>> ENSG00000136869 is located on the forward strand, gets high counts
with strandSpecific = 1.
>>>
>>> #####
>>>
>>> c = featureCounts("counts/merged.bam", annot.ext =
"../../annotations/GRCh38/genes/Homo_sapiens.GRCh38.76.gtf",
strandSpecific = 2, isGTFAnnotationFile = TRUE, isPairedEnd = TRUE)
>>>
>>>> c$stat
>>> Status counts.merged.bam
>>> 1 Assigned 10884
>>> 2 Unassigned_Ambiguity 0
>>> 3 Unassigned_MultiMapping 56
>>> 4 Unassigned_NoFeatures 5630
>>>
>>>> c$counts[c("ENSG00000066336","ENSG00000136869"),]
>>> ENSG00000066336 ENSG00000136869
>>> 10807 76
>>>
>>> ENSG00000066336 is located on the reverse strand, gets high counts
with strandSpecific = 2.
>>>
>>> Furthermore,
>>> a$counts[c("ENSG00000066336","ENSG00000136869"),] =
c$counts[c("ENSG00000066336","ENSG00000136869"),] +
b$counts[c("ENSG00000066336","ENSG00000136869"),]
>>>
>>> I downloaded the Ensembl 76 GTF file from here:
>>> ftp://ftp.ensembl.org/pub/release-76/gtf/homo_sapiens
>>>
>>> The sample BAM files is available from here:
>>> https://dl.dropboxusercontent.com/u/6006832/merged.bam
>>>
>>> Is this a bug of featureCounts or am I doing something obviously
wrong?
>>>
>>> Kind regards,
>>> Kaur Alasoo
>>> PhD student at Sanger Institute
>>>
>>> -- output of sessionInfo():
>>>
>>> R version 3.0.2 (2013-09-25)
>>> Platform: x86_64-apple-darwin10.8.0 (64-bit)
>>>
>>> locale:
>>> [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
>>>
>>> attached base packages:
>>> [1] stats graphics grDevices utils datasets methods
base
>>>
>>> other attached packages:
>>> [1] Rsubread_1.12.6 BiocInstaller_1.12.1
>>>
>>> loaded via a namespace (and not attached):
>>> [1] tools_3.0.2
>>>
>>> --
>>> Sent via the guest posting facility at bioconductor.org.
>>
>>
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