[maker-devel] Couple quick questions about Maker

[Daniel Ence]

Hi Nathaniel,

1) We'll need to see the error messages that MAKER was giving to understand what might have gone wrong with the Repeat Masker gff3 file. If you could run maker on one of your scaffolds with your current settings and send us the complete output, we can start to figure out what happened.

2) MAKER interacts with its gene predictors (augustus, snap, and the other ones listed in the control files) in a way that improves their performance (with the hints and such). When you supply predictions through the pred_gff parameter, MAKER can't give that performance improvement, so there's something of a tradeoff there. I think the performance improvement is a key part of MAKER's success, so I would definitely recommend running the ab-initio tools internally.

MAKER tries to save you time by saving results from run to run and only rerunning tools (usually blast tools) that had their parameters changed in the control files. Taking advantage of that will probably be the biggest time saver for you. Something else that could save you almost as much time would be to set a reasonable lower-bound on the size of contigs that maker will try to annotate (usually <5kbp or <10kbp depending on your genome). This parameter is set with the min_contig parameter.

I'll have to check with my lab mates about the Repeat ORF searching and how they use CEGMA results. I think you can probably just put them all in there at once though.

~Daniel




Daniel Ence
Graduate Student
dence at genetics.utah.edu<mailto:dence at genetics.utah.edu>
Eccles Institute of Human Genetics
University of Utah
15 North 2030 East, Room 2100
Salt Lake City, UT 84112-5330

On Jul 7, 2014, at 9:26 AM, Nathaniel Jue <n.jue at uconn.edu<mailto:n.jue at uconn.edu>>
 wrote:

Hi,

I'm trying to run maker on a couple genomes right now and was wondering if folks had any thoughts on way to speed it up a bit. I'm running it on a 48-processor supercomputer (lots of RAM, usually use it for genome assembly). Both these genomes are a little fragmented, so there are lots of contigs, which slows down the whole process. I am looking for ways to speed things up and was wondering about a couple things:

1) I'm currently just at the first round of maker predictions using EST and protein evidence to build models. Had already done RepeatMasking so thought I'd just input subsequent GFF to speed it up. Didn't seem to like the GFF, so two questions: i) any thoughts on why that GFF wasn't acceptable? It's the one that repeatmasker outputs if you ask it to; and ii) Providing this GFF, should generally allow the program to bypass the RepeatMasking step, correct? Does it also make it bypass the Repeat ORF searching step?

2) I plan to run both SNAP and Augustus on these genomes as well. The two-step SNAP training from the tutorials seems straightforward, but I was wondering about the Augustus step. From what I can tell, simply providing an Augustus "trained" species name should turn on Augustus and blast/blat-like hints generated within Maker are then used in gene prediction. Any thoughts on if it's either more accurate or faster to do the Augustus predictions outside of the Maker pipeline and then import them using the pred_gff parameter in the maker_opts file?

3) Finally, I noticed that you had a script for converting cegma gff files to zff file for snap training? Currently, I am using predicted transcript for this species and protein sequences from related species to training. Does anyone have any insight into using CEGMA results as well? Do you work iteratively with them? For instance, start with the using hints from more distant taxa (i.e. CEGMA) and then work your way closer? Just throw everything in at once and retrain after that?

Thanks in advance for any advice and insight.

Cheers,
Nate


Nathaniel Jue, Ph.D.
Department of Molecular and Cell Biology
University of Connecticut
Storrs, CT 06269

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