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Hi Saad,
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</div>
<div>Maker doesn't view EST or protein evidence as a gene model in themselves. There's a good reason for this. Aligners like blast don't guarantee complete gene models, with accurate start and stop codons and splice sites. With it's default settings maker
won't make a gene model unless there's evidence that overlaps an ab-initio prediction (or something from the pred_gff option). </div>
<div><br>
</div>
<div>You can use est2genome to promote everything from the est_gff option to a gene model, but this will probably give you many spurious results. What you're saying with est2genome is, "Everything that this tool found is a complete gene model." I don't think
that's true even for cufflinks output. </div>
<div><br>
</div>
<div>One of the gene predictors that can run internally is snap. It's really easy to train; here's a link to a tutorial for training it: <a href="http://weatherby.genetics.utah.edu/MAKER/wiki/index.php/MAKER_Tutorial_for_GMOD_Online_Training_2014#Training_ab_initio_Gene_Predictors">http://weatherby.genetics.utah.edu/MAKER/wiki/index.php/MAKER_Tutorial_for_GMOD_Online_Training_2014#Training_ab_initio_Gene_Predictors</a></div>
<div><br>
</div>
<div>Let me know if that helps, or if you have more question</div>
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</div>
<div><br>
</div>
<div>~Daniel</div>
<div><br>
</div>
<div>
<div apple-content-edited="true">
<div><span style="font-family: Tahoma; font-size: small; ">Daniel Ence</span></div>
<div><span style="font-family: Tahoma; font-size: small; ">Graduate Student</span></div>
<div><a href="mailto:dence@genetics.utah.edu">dence@genetics.utah.edu</a><br style="font-family: Tahoma; font-size: small; ">
<span style="font-family: Tahoma; font-size: small; ">Eccles Institute of Human Genetics</span><br style="font-family: Tahoma; font-size: small; ">
<span style="font-family: Tahoma; font-size: small; ">University of Utah</span><br style="font-family: Tahoma; font-size: small; ">
<span style="font-family: Tahoma; font-size: small; ">15 North 2030 East, Room 2100</span><br style="font-family: Tahoma; font-size: small; ">
<span style="font-family: Tahoma; font-size: small; ">Salt Lake City, UT 84112-5330</span></div>
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<div>On Jun 18, 2014, at 5:09 AM, Saad Arif <<a href="mailto:saad.arif@tuebingen.mpg.de">saad.arif@tuebingen.mpg.de</a>></div>
<div> wrote:</div>
<br class="Apple-interchange-newline">
<blockquote type="cite">Thank you for the response. I still have one question though, with these options:<br>
<br>
est_GFF=cufflinksout.GFF<br>
<br>
modle_GFF= ensembl reference.GFF<br>
<br>
What happens to cufflinks assembled transcripts that are not confined to current gene loci (i.e. novel genes in cufflinks ouput)? Would i have to prepare ab initio gene predictions for each of these predicted 'new' genes?
<br>
Is there a simple way to combine adding (new genes) and improving of an existing annotation?<br>
<br>
Any feedback on this would be greatly appreciated.<br>
<br>
saad<br>
<br>
On 13 Jun 2014, at 17:59, Carson Holt wrote:<br>
<br>
<blockquote type="cite">Use the cufflinks instead of the tophat features (tophat tends to be<br>
really noisy). Give the existing models to model_gff (they will then<br>
always be kept unless something better is found). There is no option to<br>
keep models and then just add isoforms. The model_gff input will either<br>
be kept as is (unchanged), or replaced with an updated model suggested by<br>
the evidence (the updated model may contain multiple isoforms though), and<br>
map_forward=1 can be used to pull names forward from the old model onto<br>
the new models.<br>
<br>
Thansk,<br>
Carson<br>
<br>
<br>
On 6/13/14, 5:03 AM, "Saad Arif" <<a href="mailto:saad.arif@tuebingen.mpg.de">saad.arif@tuebingen.mpg.de</a>> wrote:<br>
<br>
<blockquote type="cite">Dear All,<br>
<br>
I would like to use Maker pipeline to expand a current annotation (new<br>
isoforms and novel genes with respect to current annotation) and was<br>
wondering if anyone had experience with this and or suggestions to my<br>
questions.<br>
<br>
Briefly:<br>
<br>
I have tophat splice junctions from RNAseq data or alternatively<br>
cufflinks generated transcript models (fasts format) that i want to use<br>
as my new data (est_gff or est).<br>
<br>
I want to provide the current Ensembl annotation for gene prediction but<br>
i want this annotation to remain unchanged. Hence, i’m not sure if i<br>
should provide this annotation as pred_gff<br>
or model_gff. Can the model_gff be used for gene prediction or is this<br>
just a subset of pred_gff that remain unaltered? Can we provide the same<br>
annotation for both options (pred_ and mod_gff)?<br>
<br>
<br>
<br>
Importantly, my main goal is to use the new RNAseq data to add more<br>
isoforms and (any) novel genes to the existing Ensembl annotation. Any<br>
thoughts or suggestions on how to go about this would be sincerely<br>
appreciated.<br>
<br>
<br>
Thanks in advance,<br>
saad<br>
<br>
<br>
<br>
<br>
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