<html><head><meta http-equiv="Content-Type" content="text/html charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">That will work.<div class=""><br class=""></div><div class="">—Carson</div><div class=""><br class=""><div><blockquote type="cite" class=""><div class="">On Mar 1, 2017, at 2:09 PM, Quanwei Zhang <<a href="mailto:qwzhang0601@gmail.com" class="">qwzhang0601@gmail.com</a>> wrote:</div><br class="Apple-interchange-newline"><div class=""><div dir="ltr" class=""><div class=""><div class="">Thank you. I have submit my jobs to our server. What I plan to do is
like this: (1) split contigs into 50 files; (2) for each contig file, I collected the annotation into gff and protein
sequences into fasta format; (3) manually merge the 50 gff files and protein sequences files. Is what I am doing also correct?<br class=""><br class=""></div>Best<br class=""></div>Quanwei<br class=""><div class=""><div class=""> <div class="gmail_extra"><br class=""><div class="gmail_quote">2017-03-01 15:54 GMT-05:00 Carson Holt <span dir="ltr" class=""><<a href="mailto:carsonhh@gmail.com" target="_blank" class="">carsonhh@gmail.com</a>></span>:<br class=""><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div style="word-wrap:break-word" class="">If you split into separate files, you can use the -g option to select the input file together with the -base option so all output goes to the same directory. Because they technically have different input files, this will avoid file locking issues. You have to use the -dsindex option at the end to rebuild the datastore index, so it looks like a single job. But that is one way to get around the issue.<span class="m_9025798712864501582HOEnZb"><font color="#888888" class=""><div class=""><br class=""></div></font></span><div class=""><span class="m_9025798712864501582HOEnZb"><font color="#888888" class="">—Carson</font></span><div class=""><div class="m_9025798712864501582h5"><br class=""><div class=""><br class=""></div><div class=""><br class=""><div class=""><blockquote type="cite" class=""><div class="">On Mar 1, 2017, at 1:52 PM, Quanwei Zhang <<a href="mailto:qwzhang0601@gmail.com" target="_blank" class="">qwzhang0601@gmail.com</a>> wrote:</div><br class="m_9025798712864501582m_-1436743052125324321Apple-interchange-newline"><div class=""><div dir="ltr" class=""><div class=""><div class=""><div class="">Thank you. But I met some problems with MPI on our server. So now I split my contigs into several files and annotate those files separately. After I finish the annotation on each file, I will merge the results. <br class=""><br class=""></div>Thank you for your explanation!<br class=""><br class=""></div>Best<br class=""></div>Quanwei <br class=""></div><div class="gmail_extra"><br class=""><div class="gmail_quote">2017-03-01 15:36 GMT-05:00 Carson Holt <span dir="ltr" class=""><<a href="mailto:carsonhh@gmail.com" target="_blank" class="">carsonhh@gmail.com</a>></span>:<br class=""><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">If you submit too many simultaneous, MAKER run then file locks will start to collide and one run will slow down the others. You should submit fewer simultaneous jobs and instead use MPI (maker must be configured and compiled to use MPI).<br class="">
<br class="">
An example MPI launch command for running on 200 CPUs on a cluster —><br class="">
mpiexec -n 200 maker 2> maker_mpi1.error<br class="">
<br class="">
—Carson<br class="">
<div class=""><div class="m_9025798712864501582m_-1436743052125324321h5"><br class="">
<br class="">
<br class="">
> On Feb 27, 2017, at 8:25 AM, Quanwei Zhang <<a href="mailto:qwzhang0601@gmail.com" target="_blank" class="">qwzhang0601@gmail.com</a>> wrote:<br class="">
><br class="">
> Hello:<br class="">
><br class="">
> I am doing genome annotation using Maker on our high performance computational cluster (HPC). Due to some issues of MPI, I submitted the Maker jobs several times under the same directory to HPC. Followed by the example in the protocol (as shown below), when I submit the jobs I make them as background processes by "&" except the first one. Is this necessary when I submit a job to a HPC? I found it costed much much longer time than I expected (according to a testing on a smaller data set). I am not sure whether setting the process as background process lead to this issue?<br class="">
><br class="">
> The example in the protocol<br class="">
> % maker 2> maker1.error<br class="">
> % maker 2> maker2.error &<br class="">
> % maker 2> maker3.error &<br class="">
> ......<br class="">
><br class="">
> BTW, will the annotation on shorter contig (e.g., 500bp) cost ~ 1/100 of the time that cost for annotation a 50000bp contig? I am using SNAP for an inito and RNA-seq assembly and protein sequences as evidence. I have more than half contigs shorter than 300bp (whose total length is only about 5% of the total length of all contigs), I want to know whether I can save about half (or only about 5%) of the time if I ignore those short contigs.<br class="">
><br class="">
> Thanks<br class="">
><br class="">
> Best<br class="">
> Quanwei<br class="">
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