Mercurial > repos > peterjc > tmhmm_and_signalp
diff tools/protein_analysis/promoter2.xml @ 16:7de64c8b258d draft
Uploaded v0.2.5, MIT licence, RST for README, citation information, development moved to GitHub
author | peterjc |
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date | Wed, 18 Sep 2013 06:16:58 -0400 |
parents | 6abd809cefdd |
children | e6cc27d182a8 |
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--- a/tools/protein_analysis/promoter2.xml Thu Apr 25 12:25:52 2013 -0400 +++ b/tools/protein_analysis/promoter2.xml Wed Sep 18 06:16:58 2013 -0400 @@ -1,13 +1,15 @@ -<tool id="promoter2" name="Promoter 2.0" version="0.0.4"> +<tool id="promoter2" name="Promoter 2.0" version="0.0.6"> <description>Find eukaryotic PolII promoters in DNA sequences</description> <!-- If job splitting is enabled, break up the query file into parts --> <!-- Using 2000 per chunk so 4 threads each doing 500 is ideal --> <parallelism method="basic" split_inputs="fasta_file" split_mode="to_size" split_size="2000" merge_outputs="tabular_file"></parallelism> <command interpreter="python"> promoter2.py "\$NSLOTS" $fasta_file $tabular_file + ##I want the number of threads to be a Galaxy config option... ##Set the number of threads in the runner entry in universe_wsgi.ini ##which (on SGE at least) will set the $NSLOTS environment variable. - ##If the environment variable isn't set, get "", and defaults to one. + ##If the environment variable isn't set, get "", and the python wrapper + ##defaults to four threads. </command> <stdio> <!-- Anything other than zero is an error --> @@ -41,10 +43,14 @@ The input is a FASTA file of nucleotide sequences (e.g. upstream regions of your genes), and the output is tabular with five columns (one row per promoter): - 1. Sequence identifier (first word of FASTA header) - 2. Promoter position, e.g. 600 - 3. Promoter score, e.g. 1.063 - 4. Promoter likelihood, e.g. Highly likely prediction +====== ================================================== +Column Description +------ -------------------------------------------------- + 1 Sequence identifier (first word of FASTA header) + 2 Promoter position, e.g. 600 + 3 Promoter score, e.g. 1.063 + 4 Promoter likelihood, e.g. Highly likely prediction +====== ================================================== The scores are classified very simply as follows: @@ -61,12 +67,22 @@ **References** -Knudsen. +If you use this Galaxy tool in work leading to a scientific publication please +cite the following papers: + +Peter J.A. Cock, Björn A. Grüning, Konrad Paszkiewicz and Leighton Pritchard (2013). +Galaxy tools and workflows for sequence analysis with applications +in molecular plant pathology. PeerJ 1:e167 +http://dx.doi.org/10.7717/peerj.167 + +Steen Knudsen (1999). Promoter2.0: for the recognition of PolII promoter sequences. -Bioinformatics, 15:356-61, 1999. +Bioinformatics, 15:356-61. http://dx.doi.org/10.1093/bioinformatics/15.5.356 -http://www.cbs.dtu.dk/services/Promoter/output.php +See also http://www.cbs.dtu.dk/services/Promoter/output.php +This wrapper is available to install into other Galaxy Instances via the Galaxy +Tool Shed at http://toolshed.g2.bx.psu.edu/view/peterjc/tmhmm_and_signalp </help> </tool>