Visualizing gene density along the chromosome
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4.8 years ago
yh362 ▴ 50

I want to visualize gene density along several chromosomes as a heatmap like the supplementary figure 13 in this link https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-019-0405-z/MediaObjects/41588_2019_405_MOESM1_ESM.pdf

Hope someone could recommend some python or R packages for doing that. Great thanks!

python R • 3.3k views
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If Perl is also OK for you: DensityMap.

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4.8 years ago
igor 13k

You should try karyoploteR. It comes with a tutorial specifically for plotting the density of genes along the genome.

enter image description here

This is just one visualization. The karyoploteR package has a lot of different settings to change the exact appearance.

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Yes that is a good option for chromosome visualisation. What is not clear to me is what is the format of the gene density input file that is needed. For the examples in karyoploteR they use human data which are already loaded in the package. Do you have any suggestion on how the input file of gene/feature density should be formated?

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Hi Midge,

Guess it can be a GRanges object, which can be created from a data frame using GenomicRanges::makeGRangesFromDataFrame():

> library(karyoploteR)
> df <- data.frame(
+   chr = c("chr1", "chr3", "chr5", "chr7", "chr9"),
+   start = 11:15,
+   end = 20:24,
+   strand = c("+", "-", "+", "-", "+"),
+   gene_id = 1:5
+ )
> df
   chr start end strand gene_id
1 chr1    11  20      +       1
2 chr3    12  21      -       2
3 chr5    13  22      +       3
4 chr7    14  23      -       4
5 chr9    15  24      +       5
> gr <- GenomicRanges::makeGRangesFromDataFrame(df)
> gr
GRanges object with 5 ranges and 0 metadata columns:
      seqnames    ranges strand
         <Rle> <IRanges>  <Rle>
  [1]     chr1     11-20      +
  [2]     chr3     12-21      -
  [3]     chr5     13-22      +
  [4]     chr7     14-23      -
  [5]     chr9     15-24      +
  -------
  seqinfo: 5 sequences from an unspecified genome; no seqlengths
> kp <- plotKaryotype(genome = "hg19")
> kp <- kpPlotDensity(kp, gr)

karyoploteR_example_output

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