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This module is for predicting disordered regions in protein sequences
The newest version!
JRONN version 3.1b usage 1 August 2011:
java -jar JRONN_JAR_NAME -i=inputfile
Where -i=input file
Input file can contain one or more FASTA formatted sequences.
All OPTIONS are optional
Supported OPTIONS are:
-o=output file
-d=disorder value
-f=V or H
-s=statistics file
-n=number of threads to use
OPTION DETAILED DESCRIPTION:
-o full path to the output file, if not specified
standard out is used
-d the value of disorder, defaults to 0.5
-f output format, V for vertical, where the letters
of the sequence and corresponding disorder values are
output in two column layout. H for horizontal, where the
disorder values are provided under the letters of the
sequence. Letters and values separated by tabulation in
this case. Defaults to V.
-s the file name to write execution statistics to.
-n the number of threads to use. Defaults to the number of
cores available on the computer. n=1 mean sequential
processing. Valid values are 1 < n < (2 x num_of_cores)
Default value will give the best performance.
EXAMPLES:
Predict disorder values for sequences from input file /home/input.fasta
output the results to the standard out. Use default disorder value
and utilise all cpus available on the computer.
java -jar JRONN.JAR -i=/home/input.fasta
Predict disorder values for sequences from input file /home/input.fasta
output the results in horizontal layout to the /home/jronn.out, collect
execution statistics to /home/jronn.stat.txt file and limit the number
of threads to two.
java -jar JRONN.JAR -i=/home/input.fasta -o=/home/jronn.out -d=0.6 -n=2 -f=H
The arguments can be provided in any order.
ABOUT THE PROGRAM:
JRONN is a Java implementation of RONN. JRONN is based on RONN and uses the
same model data, therefore gives the same predictions. Main motivation
behind JRONN development was providing an implementation of RONN more
suitable to use by the automated analysis pipelines and web services.
Original version of RONN is described in Yang,Z.R., Thomson,R.,
McMeil,P. and Esnouf,R.M. (2005) RONN: the bio-basis function neural network
technique applied to the detection of natively disordered regions in proteins
Bioinformatics 21: 3369-3376
See also http://www.strubi.ox.ac.uk/RONN
Author: Peter Troshin
email: to.petr AT gmail DOT com
This is a free software which comes with no guarantees.
JRONN is distributed under Apache Licence version 2. The full version of
licence can be obtained from http://www.apache.org/licenses/LICENSE-2.0