Program is implemented in the Java programming language and distributed as a runnable jar file (MotifSearch.jar). It requires JRE (Java Runtime Environment) version 1.6 or latest.
Program can be started with the following command:

java -jar MotifSearch.jar [parameters]

where supported parameters are: 
 -i <input_file>        input file name (mandatory)
 -m <motif_length>      length of the motif (mandatory)
 -s <motif_similarity>  number of similar nucleotides (mandatory)
 -b <sequence_begin>    begin of subsequence to analyze (default: 0)
 -e <sequence_end>      end of subsequence to analyze (default: all)
 -n <sequences_loaded>  number of loaded sequences (default: all)
 -p <patterns_analyzed> number of analyzed patterns (default: all)
 -r <random_ratio>      random sequence ratio (default: 1.0)
 -c <reference_file>    reference file name
 -o <output_file>       output file name (default: input file + '.out')
 -t <separator_symbol>  output file separator (default: tab)
 -d <deviation_level>   level of distinct occurrences deviation (default: 0.05)
 -v <random_deviation>  level of random occurrences deviation (default: 5)
 -x <weight_matrix>     type of weight matrix used for calculation (default: log)
 -f <reported_motifs>   number of reported sequences (default: all)


When working with large input file it is recommended to increase the maximum Java heap size with the corresponding option -Xmx.
Example command line to start the program:

java -Xmx1g -jar MotifSearch.jar -i test.fa -m 7 -s 6 -b 0 -e 100

Program generates 4 output files:
-	‘.mtx’ file for each motif reports the maximum value of the position weigh matrix score found in each of the input sequences,
-	‘.out’ file in the consecutive columns reports: motif, number of occurrences of the motif in the input sequences, number of occurrences of the motif in the random sequences, deviation calculated as the ratio of the abundance of motifs in the input sequences and in the random sequence,   
-	‘.occ’ file in the consecutive columns reports: motif, number of occurrences of the motif at the consecutive positions of the input sequences,
-	‘.pwm’ reports the list of substring in the cluster with the number of occurrences of each substring in the input sequences and the position weight matrix for the motif.