The MEME Suite

• The MEME Suite version number and release date.
• The program name, file contents and date the file was created.
• A link to the MEME Suite home page.
• A reference to cite if you publish results from the MEME Suite.
• Some global information about the MHMM.
• A list of the states in the MHMM.
• The matrix of transition probabilities between states of the MHMM.

The list of states in the MEME Suite HMM begins with eight lines that specify the global characteristics of the model. These lines tell

• whether the model has a linear or completely connected topology (i.e., whether the model allows for repetition and shuffling of motifs),
• the total number of states in the model,
• the total number of spacers (i.e., inter-motif regions) in the model,
• the number of states used to represent each spacer,
• the number of letters in the alphabet (4 for DNA and 20 for amino acids),
• the alphabet,
• the background frequencies used as emission probabilities in the spacer states, and
• the name of the MEME output file that was used to generate this MHMM.

Following the global characteristics is a list of state descriptions. Each state description consists of six lines. These lines tell

• the index of the state (numbered from 0),
• the type of state (i.e, whether it is a start or end state, a spacer state, or the beginning, middle or end of a motif),
• the index of the motif within which this state appears (This value is arbitrarily set to -1 for non-motif states.),
• the position of the state within the motif or spacer region, and
• the letter that is printed above this state when the MEME motif ID is printed centered with respect to the motif,
• the list of probabilities that this state will emit each of the letters in the alphabet.

The final item (the list of emission probabilities) is omitted from the start and end states, which do not emit letters.

The MHMM file ends with a square matrix containing n rows and n columns, where n is the number of states in the model. The entry in row i, column j of this matrix is the probability of transitioning from state i to state j in the model. Consequently, each row in the matrix sums to 1.0.