Many examples can be found in the man pages. This page will be updated with additional examples.
These files may be used to try the examples below
example.matstorm -n 1 -q -h -s example.faa example.matReports one highest scoring site in each sequence, computed from both the positive and negative strands in the sequences in example.faa and the motifs in example.mat. The output is printed on standard output. The command:
storm -m -s example.faa example.matdoes the exact same thing, because "-m" is an alias for "-n 1 -q -h".
storm -t 14 -s example.faa example.matReports all occurrences with score 14 or greater in the sequences from example.faa for each motif in example.mat. The results are printed to standard output. Because the score threshold is given as an absolute score, this would only be useful if the motifs contained in example.mat all had a width and information content that made '14' a meaningful threshold. A more useful set of parameters would be the following:
storm -f -t 0.9 -s example.faa example.matwhere the threshold is given in terms of functional depth, and would have a similar meaning for all motifs.
storm -n 3 -h -s example.faa -o output example.matReports the top 3 sites from the entire set of sequences, and if there is a tie for third, all sites with that score will be reported. In contrast, the command
storm -n 3 -s example.faa -o output \ example.matwill always report exactly three sites for each motif, even if there are, e.g., 10 sites with the top score.
storm -n 3 -s example.faa -o output.mat \ -b example.bg example.matThis is the same as above except that sequences in example.bg are used, along with those in example.faa, to obtain a base composition. Also, the output will be written to output.mat instead of standard output.
storm -n 2 -s example.faa -o output.mat \ --base-comp=0.2,0.3,0.27,0.23 example.matReports the top 2 sites in the entire set of sequences from example.faa using the base composition of A=0.2 C=0.3 G=0.27 T=0.23 when building the scoring matrices.
storm -N -m -s example.faa example.matSame as the first example, except the sequences will not be pre-processed as suffix trees, but instead scanned sequentially for each motif. This is useful if there are very few motifs, and there will be no benefit in amortizing the cost per motif by building the suffix trees.
storm -H example.tab -p -t 0.00001 \ -s example.faa example.matThis example uses the processed information in the gk-table file example.tab to determine which sites in example.faa have a p-value less than 0.00001; if the sequences in example.faa are 1000 bases in length, then each motif is expected to have roughly one occurrence per 100 sequences. Examples of gk-table files can be downloaded by following the link on the left of the screen.