Question

Custom gene annotations for SGSeq

0

Entering edit mode

116100016 • 0

@116100016-22156

Last seen 5.0 years ago

I tried using the do novo splice prediction to see if it could detect other splice variants in the androgen receptor. Though it correctly identified the exons, it couldn't identify any of the splice variants in the annotated file. So I was wondering if it is possible to input a custom annotation, or in my case, just add a few more junctions to cover the newly added AR variants from the literature?

sgseq alternative splicing rna seq • 1.2k views

ADD COMMENT • link updated 4 months ago by Sara • 0 • written 5.1 years ago by 116100016 • 0

score 2 · Answer 1 · 2019-11-27

2

Entering edit mode

Leonard Goldstein ▴ 260

@leonard-goldstein-6845

Last seen 7 months ago

Australia

Yes you can work with a combination of annotated and predicted gene models. The easiest way to do this is to use analyzeFeatures() for annotated gene models as explained in the vignette but with predict = TRUE.

ADD COMMENT • link 5.1 years ago Leonard Goldstein ▴ 260

0

Entering edit mode

What if instead of de novo prediction I just want to add a few hg19 junction coordinates (i.e. [66950000, 66953200]) to the Features object? Is there a way to just add a few in?

ADD REPLY • link 5.1 years ago 116100016 • 0

2

Entering edit mode

You can add junctions manually for a TxFeatures object. But you have to be careful that coordinates are consistent with exons. Junction starts and ends have to coincide with exon ends and start, respectively. Here is an example for TxFeatures object txf_ann that comes with the package:

new_junction <- TxFeatures(GRanges("16:87365116-87368910:-", type = "J"))
new_txf <- c(txf_ann, new_junction)

ADD REPLY • link 5.1 years ago Leonard Goldstein ▴ 260

0

Entering edit mode

Hi Leonard,

I have a question regarding to splice graph analysis based on de novo prediction. from the documentation that I followed I notoced for teh de novo prediction you made the TxFeatures object for only specific gene and it saved as in "gr".

sgfc_pred <- analyzeFeatures(si, which = gr)

and for the annotated prediction you used TxFeatures from TxDb.Hsapiens.UCSC.hg19.knownGene.

sgfc_ucsc <- analyzeFeatures(si, features = txf_ucsc)

The thing that I didn't really understood, how I have to make de novo prediction for all of my genes how I have to creat the object to use as which in the function?

thank you so much in advance! Looking forward to hearing back from you.

ADD REPLY • link 4 months ago Sara • 0