[maker-devel] Fused gene problem, improvement in the Maker 2.27?

[Barry Moore]

Hi Sean,

I think you want to be careful with dropping the pred_flank parameter too low.  This controls how much flanking sequence (for a given cluster of evidence) MAKER will pass to the gene predictor.  Some (maybe all?) of the gene predictors have an initial state in their HMM for intergenic sequence and if you do not have some intergenic sequence for them to consider first they can't transition to their next state.  The correct_est_fusion option can help (at the cost of losing some UTR annotations) - Carson will likely give you a better description of the intricacies of the correct_est_fusion.

Don't know how you are assembling your RNASeq, but there is an option in Trinity - I forget the name - that will instruct Trinity to be more restrictive in merging neighboring clusters of reads into a longer transcript and this can help as well.

B

On May 21, 2013, at 1:36 AM, <Sean.Li at csiro.au>
 wrote:

> Hi Carson,
>  
> We are currently working on the annotation of Helicoverpa genome project. Maker has been chosen as the preliminary tool for the task. By checking the annotation results by using maker 2.10, we saw some loci have the fusion problem: two separate neighbour genes are likely to be fused together and regarded as a single candidate output by maker. If we go further by looking at the outputs from each individual de novo algorithm, e.g. augustus or snap, the prediction was correct.  We are also using RNA-Seq assembly from cufflinks and some protein evidence data from closely related insects.  
>  
> We noticed that the parameters “pred_flank” in maker v2.10 and “correct_est_fusion” in maker v2.27 might be useful for maker to decide when to merge models or not.  If possible, can you please explain what these two parameters can do with the predicted genes, RNA-Seq and protein evidence?
>  
> Also, our current plan is  to install maker 2.27,  train the algorithms to predict UTRs, enlarge the protein evidence datasets and input our previous annotations as model_gff. We are facing with an critical question: in which way we could effectively improve the gene fusing problem? 1) setting the pred_flank lower than 100? 2) turn the correct_est_fusion on? 3) anything else?  
>  
> Thank you.
>  
> With best regards,
> Xi (Sean) Li, Ph. D.
> 
> Bioinformatics Analyst, Bioinformatics Core,
> CSIRO Mathematics, Informatics and Statistics
> Phone: +61 2 6216 7138
> Address: GPO Box 664, Canberra, ACT 2601
>  
>  
>  
>  
>  
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Barry Moore
Research Scientist
Dept. of Human Genetics
University of Utah
Salt Lake City, UT 84112
--------------------------------------------
(801) 585-3543




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