MoTeX

a word-based HPC tool for MoTif eXtraction

Manual

Usage


Output

Each line of the output represents a valid motif, which is space-separated as follows:
  1. the motif
  2. the number of sequences in which the motif occurs
  3. the total number of input sequences
  4. the ratio of 2. to 3.
  5. the total number of occurrences of the motif


Examples


Example 1.
In order to reproduce the results on the accuracy of MoTeX presented in

Solon P. Pissis, Alexandros Stamatakis, and Pavlos Pavlidis. MoTeX: A word-based HPC tool for MoTif eXtraction. In Proceedings of the Fourth ACM International Conference on Bioinformatics and Computational Biology (ACM-BCB 2013), pp.13-22, 2013

change to directory `data' and follow the instructions in file README.


Example 2.
Here is a series of steps to extract single motifs and assess their statistical significance:

1. Uncompress the input file `dnc_subtilis_330-30.seq.bz2'

	bunzip2 ./data/dnc_subtilis_330-30.seq.bz2

2. Extract single motifs with 8 threads

	./motexOMP -a DNA -i ./data/dnc_subtilis_330-30.seq -o single.motex -d 0 -k 6 -e 1 -q 12 -S single.smile -t 8

3. Assess their statistical significance

	cd SMILE
	./smile ../data/dnc_subtilis_330-30.seq ../single.smile single.smile.output 100 2


Example 3.
Here is a series of steps to extract structured motifs and assess their statistical significance:

1. Uncompress the input file `dnc_subtilis_330-30.seq.bz2'

	bunzip2 ./data/dnc_subtilis_330-30.seq.bz2

2. Extract structured motifs with 8 threads

	./motexOMP -a DNA -i ./data/dnc_subtilis_330-30.seq -o struct.motex -d 0 -k 6 -e 1 -q 1 -s ./data/boxes.txt -S struct.smile -t 8

The first line of the file `./data/boxes.txt' is an integer number representing the total number of spacers of the structured motif. Every succeeding four lines are four integer numbers representing the min and the max length of the corresponding spacer, the length of the succeeding box, and the maximum number of errors allowed in the box, respectively.

3. Assess their statistical significance

	cd SMILE
	./smile ../data/dnc_subtilis_330-30.seq ../struct.smile struct.smile.output 100 2


Example 4.
Here is a series of steps which could potentially be used as a biological pipeline:

1. Run a background (bg) input dataset, and output it to `bg.motex'.

	./motexOMP -a DNA -i bg.dataset -o bg.motex -d 0 -q 1 -k 10 -e 1 -t 4

2. Run a foreground (fg) input dataset, and output the fg motifs to `fg1.motex'; output the fg motifs that are not matched with any bg motif to `un.motex'.

	./motexOMP -a DNA -i fg.dataset -b bg.motex -o fg1.motex -u un.motex -d 0 -q 1 -k 10 -e 1 -t 8

3. Check whether the fg motifs in `un.motex' are motifs in the bg dataset, and, if yes, output them to `fg2.motex'.

	./motexOMP -a DNA -i bg.dataset -I un.motex -o fg2.motex -d 0 -q 1 -k 10 -e 1 -t 8