[BioC] Calculate coverage on genome.

[Fabrice Tourre]

Dear Martin,
Thank you very much for your help.
It seems I have got it with your help.
In fact, I have read the manual of IRanges a few days ago. But it is
difficult to understand what is doing of methods flank, narrow,
restrict, etc. I think the best written documents are bedtools. Just a
complain. I will have a closer look again.
Thanks.

On Wed, Mar 16, 2011 at 2:25 PM, Martin Morgan <mtmorgan at fhcrc.org> wrote:
> On 03/16/2011 01:46 AM, Fabrice Tourre wrote:
>>
>> Dear Martin,
>> I am appreciated for you suggestion.
>> I found in GenomicFeatures, there are such method:
>> transcriptsBy, exonsBy, cdsBy, intronsByTranscript,
>> fiveUTRsByTranscript, threeUTRsByTranscript.
>>
>> So maybe I can used these method to got the coverage on exons, cds,
>> transcripts, introns, 3'utr and 5'utr. Do you have some ideas how to
>> got the coverages on promoter regions? For example, up to TSS 5kb
>> regions.
>
> Hi Fabrice -- if you have the TSS (e.g., from start(transcriptsBy(<...))),
> you can easily create GRanges representing them, either directly using
> ?GRanges or ?GRangesList, or by manipulating an existing GRanges /
> GRangesList object with commands like flank, narrow, etc., as documented on
> for instance the GRanes help page. Martin
>
>> Thanks.
>>
>> On Tue, Mar 15, 2011 at 9:17 PM, Martin Morgan<mtmorgan at fhcrc.org>  wrote:
>>>
>>> On 03/15/2011 12:19 PM, Fabrice Tourre wrote:
>>>>
>>>> What's more, how many covaged the repeat region and unique region?
>>>
>>> Hi Fabrice --
>>>
>>> The steps in the work flow might invovle: input reads
>>>
>>>  library(GenomicRanges)
>>>  aln<- readGappedAlignemnts(<...>))
>>>
>>> and create regions of interest, e.g., from
>>>
>>>  library(GenomicFeatures)
>>>  txdb<- makeTranscriptDbFromUCSC(<...>)
>>>  cds<- cdsBy(txdb, "gene")
>>>
>>> or using the biomaRt or AnnotationDbi packages. Then count reads in each
>>> region of interest
>>>
>>>  hits<- countOverlaps(aln, cds)
>>>
>>> or calculate coverage and take views based on your regions of interest
>>>
>>>  cvg<- coverage(aln)
>>>  v<- Views(cvg, ranges(cds))
>>>
>>> and then summarize, e.g., viewSums. Maybe others will contribute more
>>> detail.
>>>
>>> Martin
>>>
>>>>
>>>> On Tue, Mar 15, 2011 at 8:18 PM, Fabrice Tourre<fabrice.ciup at gmail.com>
>>>>  wrote:
>>>>>
>>>>> Dear list,
>>>>> I am analysis mouse MeDIP-seq data, I want to know what percent reads
>>>>> coveraged the promter, 3'UTR, 5'UTR, intron and Exon region. Is there
>>>>> any packages can do this?
>>>>> Thank you very much in advance.
>>>>>
>>>>
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>>>
>>> --
>>> Computational Biology
>>> Fred Hutchinson Cancer Research Center
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>>>
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>
>
> --
> Computational Biology
> Fred Hutchinson Cancer Research Center
> 1100 Fairview Ave. N. PO Box 19024 Seattle, WA 98109
>
> Location: M1-B861
> Telephone: 206 667-2793
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at r-project.org
> https://stat.ethz.ch/mailman/listinfo/bioconductor
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>