processor ID: 15427
==========================================================================

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|              *** Running a seeded analysis ***                   |
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command line: /home/grobertson/Fi/Code/20090926_v1.3/Fi_v1.3/bin/fi -fseq /projects/remc_bigdata/Karsan/HS1238_kd/compare/FA/HS1238-cmp-lowP_17000-sU.hg18.fa.3stage_dm_w4.fa -fout /projects/remc_bigdata/Karsan/HS1238_kd/compare/seed_CSL_TGTGGGAA/b/HS1238-cmp-lowP_17000-sU.hg18.fa.3stage_dm_w4.fa.pwmCSL_TGTGGGAA.mx.weight0.de_novo -minN 2000 -ev 5000 -pv 0.0002 -fpwm0 /home/grobertson/Fi/PWMs/CSL_TGTGGGAA.mx -em 80 -fEM 0.5 -posWt 0 -extTrim EXTRIM -verbose 1 -pgf 0 -fbm /home/grobertson/Fi/Code/20090926_v1.3/KmerFreq/hg18_kmer_1to9_freq.txt -bOrder 3 

maximal buffer length:					15000
maximal number of sequences set:			100000
maximal number of bases per seq read:			20000
maximal number of sites in a motif:			150000
input (ChIP) sequence file:				/projects/remc_bigdata/Karsan/HS1238_kd/compare/FA/HS1238-cmp-lowP_17000-sU.hg18.fa.3stage_dm_w4.fa
number of sequences in input file:			17000
average sequence length:				1085
total number of nucleotides:				18455169
max number of generations:				1
population size:					10
use a user-specified pwm as the seed			/home/grobertson/Fi/PWMs/CSL_TGTGGGAA.mx
fraction (number) input sequences subject to EM		1.00 (17000)
scale factor for converting (double)pwm to (int)pwm	 200
number of EM steps:					80
EM convergence criterion:				1.000000e-04
run EM on the starting pwm /home/grobertson/Fi/PWMs/CSL_TGTGGGAA.mx 10 times, each with a different maxp:
0.10*numSeq 0.20*numSeq 0.30*numSeq 0.40*numSeq 0.50*numSeq 0.60*numSeq 0.70*numSeq 0.80*numSeq 0.90*numSeq 1.00*numSeq 
no spaced dyads are generated and used. pop=10 gen=1 (no GA).

motif prior probability type (see documentation):	0
pwm score p-value cutoff for declaring binding site:	2.000000e-04

Approximate the null llr log{p(s|M)/p(s|B)} score distribution using
the llr scores of random/background sequences, where M is the EM-derived
motif model and B is the 3-th order Markov backgroun model.

The background sequences are simulated using the [a,c,g,t] frequencies
in the input data. The number sets of background sequences generated: 	10

pseudo count:						0.0005
minimal infomation for trimming/extending: 		0.40 0.50 0.60
minimal no. sites for each motif:			2000
base extension and trimming? 				no
sliding window for comparing pwm similarity:	6
PWM similarity cutoff:					0.300
log(E-value) cutoff:					5000.00
number of adjacent bases included in binding site output:	10

job started: Sun Jul 11 12:45:57 2010

=========================================================================

GADEM cycle[  1] generation[  1] number of unique motif(s): 1
   spacedDyad: nnTGTGGGAAnn         motifConsensus: rnkGwGGsAGGr          1.00 fitness: -16596.09

GADEM cycle[  2] generation[  1] number of unique motif(s): 1
   spacedDyad: nnTGTGGGAAnn         motifConsensus: ArrrrArrrAAr          1.00 fitness: -4739.92