Tool:deepTools: user-friendly tools for the normalization and visualization of deep-sequencing data

Question

[Björn]

deepTools addresses the challenge of handling the large amounts of data that are now routinely generated from DNA sequencing centers. To do so, deepTools contains useful modules to process the mapped reads data to create coverage files in standard bedGraph and bigWig file formats. By doing so, deepTools allows the creation of normalized coverage files or the comparison between two files (for example, treatment and control). Finally, using such normalized and standardized files, multiple visualizations can be created to identify enrichments with functional annotations of the genome.

Publicaton: http://nar.oxfordjournals.org/content/early/2014/05/05/nar.gku365.full

Source Code and Wiki: https://github.com/fidelram/deepTools/wiki

Galaxy Tool Shed repository: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools

and example Galaxy workflows: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools_workflows

Answer 1

[mikhail.shugay]

Good job! Congratulations on the paper.

I'm quite interested if it is possible to integrate side tools to your framework. Actually when working with exome data I've come across the alternative coverage measure that uses distinct reads, i.e. reads that cover a given position and have different offsets. It is also referred as molecular coverage. The inspiration comes from this paper, Fig1. Such measure could be more prone to sequencing artifacts. If you're interested the basic implementation using Picard API is here and here compiled as jar.

[Björn]

Hi,

such an enhancement would be relatively easy to implement in deepTools. I have created a github issue under https://github.com/fidelram/deepTools/issues/56 and we will try to implement it. PR are always welcome :)

Thanks for that suggestion!

Bjoern

[mikhail.shugay]

Hello! Updated the issue just a while ago, hope this would be of a potential interest

Answer 2

[xfliwz]

Hello,

Deeptools is a powerful method to visualize NGS data sets.

I used bamCorrelate bins with --binSize 1000(left) and 10000(right) respectively(both of them were plot with --corMethod pearson). And got two distinct pictures.

So, I wonder that which value is better to show the correlation of different factors?

[Björn]

Hi,

The binSize parameter depends on several factors, like depth of sequencing or scaffold of enriched peeks (sharp or broad). IMHO if you have broader regions or less sequencing depth you should use a higher binSize (10kb). Smaller values can be used by sharp regions or a high coverage.

Hope this helps,
Bjoern