Closed cc-prolix closed 2 years ago
Hello,
Yes you're right. These tags involve an overlap at the exonic level between the antisense lncRNAs and the sense mRNAs.
Note that if gene boundaries are not well annotated, intergenic
classes with convergent
or divergent
subclasses could also be of interest depending on the distance between the 2 elements.
Hope this helps.
Thank you very much for your quick response!
I have one more question: So far I had only considered transcripts with the tag "isBest = 1" in the classifier output file. What would you recommend? When would I choose an alternative classifiaction result to the one tagged "isBest = 1"?
Thank you very much!
Sorry for the late reply...
This depends on your biological question. For intergenic lncRNAs (lincRNAs), the tag "isBest = 1" is attributed to the lncRNA which is the closest to any other genes. You may want to extract all neighboring genes (not only the closest) by filtering on a certain window around the lncRNAs (e.g 1Mb) using the distance column (8th).
Hope this helps
Hello, I am also using the FEELnc_classifier.pl script to classify lncRNAs based on their genomic localization. I find some lncRNAs can not be annotated although i have increased the option "--maxwindow ". Any suggestions to annotate these lncRNAs ? What should i define the location of these lncRNAs ?
Hi,
We also observed such cases. Are these lncRNAs localized on contigs/unassembled chromosomes (without any other annotated genes located on these "chromosomes")?
Yes, these lncRNAs all localized in the unassembled chromosomes. I have solved the problem by using the GTF files with unassembled chromosomes. Thanks you very much for your reply.
Hello,
I am using the FEELnc_classifier.pl script to classify lncRNAs based on their genomic localization. I am especially interested in natural antisense transcripts: In this case lncRNAs in antisense direction with at least a partial complementarity to corresponding (protein-coding or non-coding) transcripts in opposite direction.
I am wondering about what subset of the classifier output would suit my needs best: I would choose transcripts tagged "antisense", a "genic" type and "exonic" location to get at least partial complementarity? Can you recommend anything?
Thank you very much for your help!