Segmental duplication and pseudogenes

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Bardai, Ghalib

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Aug 22, 2022, 3:53:38 PM8/22/22
to gen...@soe.ucsc.edu

Hello,

 

How can I extract, from the UCSC Genome Browser Database, a list of genes and exons that are affected by >90% homology based on segmental duplication data for hg19?

 

Thanks

 

Ghalib


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Brian Lee

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Aug 25, 2022, 5:45:23 PM8/25/22
to Bardai, Ghalib, gen...@soe.ucsc.edu

Dear Ghalib,

Thank you for reaching out to us with your question about genomic data.

It will help to take some time looking at our archives of historical answers, here are two searches of the terms "segmental duplications" and "pseudogenes":

This recent answer may be of interest: https://groups.google.com/a/soe.ucsc.edu/g/genome/c/OAKkMJ1v3rc/m/G_xfC57fAQAJ

That archived answer mentions the Segmental Duplications track that shows regions of the genome with over 90% similar and also exists on the hg19 (db=hg19) assembly: http://genome.ucsc.edu/cgi-bin/hgTrackUi?db=hg19&g=genomicSuperDups

It sounds like you might want to intersect that data with pseudogene data? Here is a session where that track of annotations on hg19 is turned on alongside a gene prediction track, http://genome.ucsc.edu/s/brianlee/pseudo_segmental_dups Pseudogene Annotation Set from GENCODE Version 41 (Ensembl 107). Note if you click into the Track Setting page for that collection of gene predictions, you can click a wrench "Configure" option to open a window to highlight data on metadata (or filter out data). In this case, there was an attempt to highlight on transcript biotype metadata tags.

If this intersection is what you might be interested in doing, first look at our archived answers about examples with other data sets and then reply with more questions if have any:

Thank you again for your inquiry and for using the UCSC Genome Browser. If you have any further public questions, please send new questions to gen...@soe.ucsc.edu. All messages sent to that address are archived on a publicly accessible forum to help others find answers to similar questions. If your question includes sensitive data, you may send it instead to genom...@soe.ucsc.edu, which is a private internal list to our support team.

All the best,


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