Window Length to Genomic Coordinates
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Entering edit mode
3.5 years ago

Hello Guys,

I am trying to convert window length into genomic coordinates using below mentioned commands, following a post Finding gene density from reference genome using R

library(Homo.sapiens)

human.genes = genes(TxDb.Hsapiens.UCSC.hg19.knownGene)

human.genes

GRanges object with 23056 ranges and 1 metadata column:

        seqnames                 ranges strand   |     gene_id
           <Rle>              <IRanges>  <Rle>   | <character>
      1    chr19 [ 58858172,  58874214]      -   |           1
     10     chr8 [ 18248755,  18258723]      +   |          10
    100    chr20 [ 43248163,  43280376]      -   |         100
   1000    chr18 [ 25530930,  25757445]      -   |        1000
  10000     chr1 [243651535, 244006886]      -   |       10000
    ...      ...                    ...    ... ...         ...
   9991     chr9 [114979995, 115095944]      -   |        9991
   9992    chr21 [ 35736323,  35743440]      +   |        9992
   9993    chr22 [ 19023795,  19109967]      -   |        9993
   9994     chr6 [ 90539619,  90584155]      +   |        9994
   9997    chr22 [ 50961997,  50964905]      -   |        9997

But I am not confirm how to integrate my data in .csv format containing fields as chr, start, end and copy number variations Please have a look below:

chr.   start.  end.    logR_Copy_Number

Please suggest.

coordinates Gene • 1.1k views
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Entering edit mode

I'm unable to understand the connection between your requirements and the post you've linked to. Also, what do you mean by "window size"? What does your dataset look like? You're only showing us the header here.

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Hi

My data look likes

chr start.  end copy-number
1   1   1000000 3
1   1000001 2000000 3
1   2000001 3000000 3

Here, we can see copy number are computed with respect to segments like 1 to 1000000 and so on. But, I want to convert them to gene coordinates.

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Do not add answers unless you're answering the top level question. Use Add Comment or Add Reply instead as appropriate. I've moved your post to the correct location this time, but please be more careful in the future.

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In my experience, segment level data output by most Copy Number tools (that use the Circular Binary Segmentation algorithm) can be fed as input to the GISTIC2.0 tool to generate gene level thresholded as well as log2 data. Why are you looking to use GenomicRanges to do this?

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