Question: How to Filter out False positive junctions detected from RNA-seq data?
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gravatar for julbtn
21 days ago by
julbtn0
Brussels, BE
julbtn0 wrote:

I would like to know if anyone has any recommendation on how to filter out false positive junctions detected from RNA-seq data. I am currently using different tools to detect splice junctions, but there are thousands of junctions that are detected. One way to filter out false positive junctions would be to set a threshold on how many reads support the junction and/or in how many samples the junction is found. However, it is difficult to set a common threshold when samples have different coverage, and some junctions with a low number of supporting reads and/or a low number of reoccurrence can still be of interest.

What kind of approach do you advise using? I know that some tools provide linear regression models to filter out FPs.

ADD COMMENTlink modified 21 days ago by i.sudbery10k • written 21 days ago by julbtn0
0
gravatar for i.sudbery
21 days ago by
i.sudbery10k
Sheffield, UK
i.sudbery10k wrote:

Portcullis uses an ML based approach to filter novel junctions from RNAseq data.

ADD COMMENTlink written 21 days ago by i.sudbery10k
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