Hi Tim, We understand that duplicates can be frustrating to work around. Unfortunately, for these two genomes, there is no summary transcript data available.
To clarify, for any particular mRna Genbank sequence, a single alignment is retained unless there is more than one alignment with very close similarity to the reference genome. Using these methods, it is expected that multiple distinct mRna sequences will align to a particular gene region. As you suggest, which to select as representational for each gene region will have to be parsed from the available alignment data. Perhaps reviewing some of the rules used for gene/transcript summary tracks in other genomes would be helpful? The UCSC Genes track in human has details regarding this towards the end of the dataflow methods. To view this track's description (data source, methods, etc), open up the human genome browser and click on the track name "UCSC Genes" in the Gene and Gene Prediction track group. I hope this information is a little bit helpful. Please feel free to contact the mailing list again whenever you have a question about the data or would like help. Best regards, Jen UCSC Genome Browser Support http://genome.ucsc.edu/contacts.html [email protected] [email protected] On 7/7/10 8:55 AM, Nowack, Tim wrote: > Hello, > I am trying to download full mRNA sequences for both Lamprey and Lancelet; > however, when I select "Lamprey mRNA" tracks from the "Tables," the sequences > retrieved are often duplicates (multiple allele versions and clones of the > same mRNA from different specimens). I understand how UCSC posts all clones > and multiple allele listings to cite credit to the files creator; however, > for the analysis I am running, the duplicates are creating bias. Is there any > way to download one, unique mRNA for each clone or allele retrieved? Or do > have to just parse out the duplicates manually? > > Thank you, > Tim Nowack > _______________________________________________ > Genome maillist - [email protected] > https://lists.soe.ucsc.edu/mailman/listinfo/genome _______________________________________________ Genome maillist - [email protected] https://lists.soe.ucsc.edu/mailman/listinfo/genome
