[maker-devel] Conensus gene model

[Carson Holt]

The contig in question is really too small to get much out of it (only 5
kb).  There was only one single exon EST alignments and a couple of
predictions with no evidence support.  Anything smaller than 10 kb is
mostly useless for annotation purposes.  You would really need a few 100kb
length or longer contigs to glean enough information for optimizing your
parameters.

The general suggestions for any maker run are to use proteins from a
closely related organism or a couple of closely related organisms for the
protein= option in maker.  Also leave single_exon set to 0, except for
certain eukaryotes that have a bias for single exon transcripts (i.e. some
fungi and oomycetes).  And leave keep_preds set to 0 because ab initio
predictors tend to over-predict by a wide margin (lots of false positives).

Additional training would really depend on what your other contigs look
like.  Do you have any large contigs?  I could look at one of those and
give suggestions but the provided contig is just too short to glean much.

Thanks,
Carson





On 12-10-15 1:41 PM, "Parul Kudtarkar" <parulk at caltech.edu> wrote:

>Hello,
>
>Please advice on the aforementioned query?
>
>Thanks,
>Parul Kudtarkar
>---------------------------- Original Message ----------------------------
>Subject: [maker-devel] Conensus gene model
>From:    "Parul Kudtarkar" <parulk at caltech.edu>
>Date:    Fri, October 12, 2012 2:46 pm
>To:      maker-devel at yandell-lab.org
>--------------------------------------------------------------------------
>
>Hi,
>
>We are using snap(training set[hmm file] generated using est,protein and
>contig file), agustus,genemarkE(we ran it outside maker and have gff3 file
>as input). The output that we get is combination of various
>gene-predictors and evidences. I have attached sample result file. What
>would you recommend to get consensus result set? Bootstrapping the
>resulting gff3 file (rerunning maker)?
>
>Thanks,
>Parul Kudtarkar
>--
>Scientific Programmer
>Center for Computational Regulatory Genomics
>Beckman Institute,
>California Institute of Technology
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>
>--
>Scientific Programmer
>Center for Computational Regulatory Genomics
>Beckman Institute,
>California Institute of Technology
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