It sounds like in your usage case you'll want to go with gfPcr. On Jul 21, 2010, at 5:39 PM, Gregory Dougherty wrote:
> Hi Jim, > > Unfortunately, the nodes in the cluster I'll probably be using only have 2GB > per CPU, so I'll be better off if I can partition the task into two 2GB > chunks. > > So, the situation is that I don't have a dedicated server. I have users who > might have (at most) 20 pairs of primers that they will want to validate at > once (i.e. "do these primers target my gene / region of interest?" "What's > the size of the product they'll produce?" "Is there anything else they > target?"). It's for a research lab at Mayo Clinic, and it MIGHT get used, at > most, a couple of times a day. > > My reading is that while we could send our users to the UCSC In-Silico PCR > Web page, we can NOT access it from our own program. Correct? > > Am I going to be spending minutes launching isPcr, and then seconds actually > getting results? Is it possible to pre-compute the indexes, and then just > load them in as necessary? > > Thank you, > > Greg > > ----- Original Message ----- > From: "Jim Kent" <[email protected]> > To: "Gregory Dougherty" <[email protected]> > Cc: [email protected] > Sent: Tuesday, July 20, 2010 7:45:52 PM GMT -06:00 US/Canada Central > Subject: Re: [Genome] Finding where Primers hit > > Hi - if you are doing a lot of primers at once usually you want to use isPcr. > If you want to have a server set up that will quickly align a few primers > at a time use gfPcr. The memory these days is generally not a problem. I > think 4 gig is enough for the whole genome for isPcr. > > > On Jul 20, 2010, at 11:56 PM, Gregory Dougherty wrote: > >> Thank you Hiram and Jim for pointing me in the right direction. >> >> Looking at the code, for my situation I have two workable choices: gfPcr or >> isPcr. >> >> Questions: >> 1: Is gfPcr actually a workable choice? I.E. will it let me search for hits >> from 18 base primers, and will it be as successful as isPcr at finding hits? >> >> 2: The ReadMe says that isPcr "builds its own index". Is it creating it's >> own index, or loaded an already calculated one from files? >> >> 3; For isPcr, roughly how much is "a lot of memory"? In particular, roughly >> how much space does it take from Chr1, and roughly how much does it take for >> the whole human genome? >> >> Thanks again, >> >> Greg >> >> ----- Original Message ----- >> From: "Jim Kent" <[email protected]> >> To: "Gregory Dougherty" <[email protected]> >> Cc: [email protected] >> Sent: Tuesday, July 20, 2010 1:52:22 PM GMT -06:00 US/Canada Central >> Subject: Re: [Genome] Finding where Primers hit >> >> Please use In Silico PCR, which was designed just for this purpose. >> >> On Jul 20, 2010, at 4:51 PM, Gregory Dougherty wrote: >> >>> Hi all, >>> >>> I hope this isn't a FAQ, I couldn't find any way to search the archives. >>> >>> I am writing a program that takes pairs of PCR Primer sequences, and >>> returns the products they will produce when used w/ human DNA. My first >>> thought was to use BLAT to figure out where the primers match the genome. >>> While this has worked well with test primers that are 20+ bases long, BLAT >>> won't run on smaller Primers, and my users have Primers as small as 18 >>> bases. >>> >>> Is BLAT a reasonable tool to use for solving this problem? If we download >>> the source, change the 20 base limit to 18, and then run that BLAT, will >>> that work? Work only if the sequence is a perfect match? Fail miserably? >>> >>> May be OT: Can I get Blast to tell me WHERE the primer hit in the item it >>> hit in? "Homo sapiens chromosome 17 genomic contig, GRCh37 reference >>> primary assembly, Length=21169982" really isn't a very useful hit report. >>> >>> Thanks in advance, >>> >>> Greg >>> _______________________________________________ >>> Genome maillist - [email protected] >>> https://lists.soe.ucsc.edu/mailman/listinfo/genome >> >> _______________________________________________ >> Genome maillist - [email protected] >> https://lists.soe.ucsc.edu/mailman/listinfo/genome > _______________________________________________ Genome maillist - [email protected] https://lists.soe.ucsc.edu/mailman/listinfo/genome
