Thanks
This works a treat & Is exactly what I was looking for
Tom


On Mon, Feb 11, 2013 at 6:08 PM, James W. MacDonald <jmacdon@uw.edu> wrote:

> Hi Tom,
>
>
> On 2/11/2013 11:35 AM, Tom Oates wrote:
>
>> Hi
>> I am very much a learner in R in general&  GenomicRanges in general
>>
>> I am struggling to find documentation to help me get my head around
>> distanceToNearest in GenomicRanges
>> If I have a GRanges object:
>>
>> GRanges with 6 ranges and 4 metadata columns:
>>        seqnames                 ranges strand |
>>           <Rle>               <IRanges>   <Rle>  |
>>    [1]       10 [ 96723746,  96723747]      - |
>>    [2]        7 [ 13641170,  13641171]      + |
>>    [3]       16 [ 17772801,  17772802]      - |
>>    [4]        3 [ 88173502,  88173503]      - |
>>    [5]       13 [106979682, 106979683]      + |
>>    [6]        9 [104393139, 104393140]      + |
>>
>> (You will notice that all the regions are only dinucleotides&  I have
>>
>> removed the metadata )
>>
>> I have a 2nd GRanges object which is ensembl rat transcripts as below:
>> 39549 ranges and 2 metadata columns:
>>            seqnames                 ranges strand   |     tx_id
>> tx_name
>>               <Rle>               <IRanges>   <Rle>    |<integer>
>> <character>
>>        [1]        1          [5473, 16844]      +   |         1
>> ENSRNOT00000044270
>>        [2]        1          [5526, 16968]      +   |         2
>> ENSRNOT00000049921
>>        [3]        1          [5526, 16968]      +   |         3
>> ENSRNOT00000051735
>>        [4]        1          [5598, 13520]      +   |         4
>> ENSRNOT00000034630
>>        [5]        1          [8268, 16850]      +   |         5
>> ENSRNOT00000044505
>>        [6]        1          [8316, 17577]      +   |         6
>> ENSRNOT00000042693
>>        [7]        1          [8884, 16850]      +   |         7
>> ENSRNOT00000044187
>>        [8]        1          [8956,  9955]      +   |         8
>> ENSRNOT00000041082
>>        [9]        1          [9055, 17351]      +   |         9
>> ENSRNOT00000050254
>>
>>
>> If I invoke:
>> xx<-distanceToNearest(diff.**cpgs.gr <http://diff.cpgs.gr>,
>> rat.transcripts, ignore.strand=F)
>>
>> xx
>> DataFrame with 1133 rows and 3 columns
>>       queryHits subjectHits  distance
>>       <integer>    <integer>  <integer>
>> 1            1        7752         0
>> 2            2       32166     11946
>> 3            3       14678     25377
>> 4            4       24286     66747
>> 5            5       10609     34242
>> 6            6       37076    122683
>> 7            7       35184         0
>> 8            8       34180     45561
>> 9            9       19351     50156
>> ...        ...         ...       ...
>> etc
>>
>> I am uncertain how I would then use the xx output to gain information
>> (i.e.
>> tx_id, tx_name) about the feature which the function has identified as
>> nearest?
>> I would be happy to supply any more info as required
>>
>
> The subjectHits column gives the row of your transcript GRanges object
> that matches the corresponding query row. I am assuming here that the '
> diff.cpgs.gr' GRanges object is longer than 6? Anyway, here is an example
> using your data and the TxDb.Mmusculus.UCSC.mm10.**knownGene package:
>
>
> > x
> GRanges with 6 ranges and 0 metadata columns:
>       seqnames                 ranges strand
> <Rle> <IRanges> <Rle>
>   [1]    chr10 [ 96723746,  96723747]      *
>   [2]     chr7 [ 13641170,  13641171]      *
>   [3]    chr16 [ 17772801,  17772802]      *
>   [4]     chr3 [ 88173502,  88173503]      *
>   [5]    chr13 [106979682, 106979683]      *
>   [6]     chr9 [104393139, 104393140]      *
>   ---
> > y <- transcripts(TxDb.Mmusculus.**UCSC.mm10.knownGene)
> > xx <- distanceToNearest(x, y, ignore.strand=F)
> > xx
> DataFrame with 6 rows and 3 columns
>
>   queryHits subjectHits  distance
> <integer> <integer> <integer>
> 1         1        4514    100935
> 2         2       45653         0
> 3         3       19383         0
> 4         4       34197         0
> 5         5       14383         0
> 6         6       54212      8108
>
>
> > y[xx[,2],]
> GRanges with 6 ranges and 2 metadata columns:
>
>       seqnames                 ranges strand |     tx_id     tx_name
> <Rle> <IRanges> <Rle> | <integer> <character>
>   [1]    chr10 [ 96617001,  96622811]      + |     33419  uc007gww.2
>   [2]     chr7 [ 13623967,  13670807]      + |     21400  uc012ezp.1
>   [3]    chr16 [ 17759663,  17779206]      + |     48288  uc007ylz.1
>   [4]     chr3 [ 88171560,  88177785]      - |     10107  uc008puf.2
>   [5]    chr13 [106963757, 107022114]      - |     43288  uc007rue.1
>   [6]     chr9 [104361832, 104385031]      + |     29956  uc009rhp.1
>   ---
>   seqlengths:
>                    chr1                 chr2 ...       chrUn_JH584304
>               195471971            182113224 ...               114452
>
> Best,
>
> Jim
>
>
>  Tom
>>
>>         [[alternative HTML version deleted]]
>>
>> ______________________________**_________________
>> Bioconductor mailing list
>> Bioconductor@r-project.org
>> https://stat.ethz.ch/mailman/**listinfo/bioconductor<https://stat.ethz.ch/mailman/listinfo/bioconductor>
>> Search the archives: http://news.gmane.org/gmane.**
>> science.biology.informatics.**conductor<http://news.gmane.org/gmane.science.biology.informatics.conductor>
>>
>
> --
> James W. MacDonald, M.S.
> Biostatistician
> University of Washington
> Environmental and Occupational Health Sciences
> 4225 Roosevelt Way NE, # 100
> Seattle WA 98105-6099
>
>

	[[alternative HTML version deleted]]

