Input is a set of DNA sequences adjacent or around a functional site
plus a sequence motif defined by a consensus sequence or a weight
matrix. The input sequence motif serves as an
initial model for starting the optimization process. The output
is a complete weight matrix-based description of a sequence motif
maximizing a quantitative criterion of local over-representation,
including the optimized border positions and cut-off value.
A detailed description of the method can be found here
MEME Motif Format
The motif library provided by SSA have been originally downloaded from The MEME Suite website. Motifs have then undergone a reformatting process (for more details, please read here).
Matrices from MEME are provided in two formats:
- as letter-probability matrices;
- as integer log-odds weight matrices.
The conversion of base counts into weights is given by the formula shown here:
where fib is the relative frequency of base b at PWM position i, qb is the background frequency of base b, and c is the fraction of pseudo-counts added to the observed base frequencies.
Unless specified otherwise, background letter frequencies are those from a uniform background (A 0.25000 C 0.25000 G 0.25000 T 0.25000).
Weights are rounded to nearest integers to allow for efficient computation of the probability distribution for scores expected from random sequences.
For more details, visit the MEME website or our PWMLib site .