SYNOPSIS

DESCRIPTION

mlv-smile is a program that was primarily made to extract promoter sequences from DNA sequences. The interest of this program is to infer simultaneously several motifs (called boxes) that respects distance constraints. The user has to write in a parameter_file the list of criteria that he wants the signal to respect. In a first step of extraction, all signals respecting these criteria are found. In a second step, they are all statistically evaluated, aiming to detect the ones that are exceptionally represented in the original sequences. Since the 1.4 version mlv-smile allows one to extract such signals on any alphabet in any kind of sequences.

OPTIONS

-g number

produces on the standard output a generic parameter file to extract number boxes signals.

HOW TO

How to use mlv-smile?

How to start?

What should I write in the alphabet file?

Example: if you want to extract simple motifs (A,C,G,T) from clean DNA sequences written with a four letters alphabet (A,C,G,T), then you may write an alphabet file containing:

    Type:Nucleotides
    A
    C
    G
    T

How to write a simple parameter file?

Example: Let's write a parameter file to extract simple motifs. If you don't already have one, let's first create a small DNA file in FASTA format, containing several sequences:

    > Seq A
    AGGCTAGTCAGGGCATGCGATCAGCAGGCATCAGGCGAGCATCGACAGCA
    > Seq B
    GGAGAGCGCAGAGCGAGCATCATCATGCAGCATCAGAGATCTTTCT

Our purpose is now to extract from these sequences all motifs of length 13 that appears at least one time in 100% of the sequences, allowing one substitution. We may write the following parameter file (helped with the 'mlv-smile -g 1' command):

    FASTA file          seq     // previously created
    Output file         results
    Alphabet file       alpha   //previously created
    Quorum              100
    Total min length    13
    Total max length    13
    Total substitutions 1
    Boxes               1

How to extract a simple motif?

Example: With the previous alphabet, sequences and parameter files, you can now launch mlv-smile: "mlv-smile param". You will obtain the following motifs in the "results" file:

    GCGAGCATCAACA 2120210310010 2
    Seq     1   Pos    12
    Seq     0   Pos    34
    2
    GCGAGCATCGTCA 2120210312310 2
    Seq     1   Pos    12
    Seq     0   Pos    34
    2

How to evaluate the significance of the motifs found?

Example: At the bottom of the previous "param" parameter file, you can add:

    Shufflings  100
    Size k-mer  2

For this example, you may find such results (in the "results.shuffle"):

    STATISTICS ON THE NUMBER OF SEQUENCES HAVING AT LEAST ONE OCCURRENCE
    Model          %right  #right %shfl. #shfl. Sigma Chi2 Z-score
    ==============================================================
    GCGAGCATCGTCA  100.00%    2   0.50%   0.01  0.10  3.96   19.90
    GCGAGCATCAACA  100.00%    2   1.00%   0.02  0.14  3.92   14.07
    STATISTICS ON THE TOTAL NUMBER OF OCCURRENCES
    Model            #right  #shfl. Sigma   Chi2    Z-score
    =======================================================
    GCGAGCATCGTCA        2   0.01   0.10    1.99    19.90
    GCGAGCATCAACA        2   0.02   0.14    1.96    14.07

The first block of results shows the statistics on the number of sequences having at least one occurrence. You can read, for each motif found, the frequency of apparition in the original and shuffled sequences, and two statistical scores (Chi2 and Z-score) deduced. Motifs are sorted according to the highest Z-scores. A high Z-score means that the motif appears in a surprising way in the original sequences.

How to extract structured motifs?

Example: Let's extract from the previous "seq" sequences structured motifs composed of 2 boxes of length 5 to 6, but the whole motif must have a length 11. The two boxes may be separated by 10 to 15 nucleotides. You allow at most one substitution in each box, and at least one occurrence of a motif must appear in 100% of the sequences, you may write the following parameter file:

    FASTA file          seq
    Output file         results
    
    Alphabet file       alpha
    Quorum              100
    Total min length    11
    Total max length    11
    Total substitutions 2
    Boxes               2
    
    BOX 1 ================
    Min length          5
    Max length          6
    Substitutions       1
    Min spacer length   10
    Max spacer length   15
    
    BOX 2 ================
    Min length          5
    Max length          6
    Substitutions       1

PARAMETER FILE CRITERIA

FASTA File <filename>

The name of the file which contains the sequences to use for inference. These sequences must be at the FASTA format. This file must contain at least two sequences, as you cannot detect motifs which are common to several sequences in one sequence!

Output file <filename>

The name of the file where results of extraction will be written.

Alphabet file <filemane>

The name of the file where you have to tell mlv-smile on which alphabet it will infer motifs. The first line of this file contains "Type:" followed by the type of symbols you use, to choose between "Nucleotides", "Proteins" or "Others". Then, on each line of the file, must be written the symbols of the sequence that may be matched by a symbol of a motif. A line containing "ANR" means that there is a symbol in the motif's alphabet which matches A, N or R in the sequences. If Type is defined with Nucleotides, mlv-smile will change this ANR symbol into an A to make it more readable. These associations will be printed at the beginning of the execution.

Quorum <number>

The percentage of sequences where at least one occurrence of a motif must appear to make it valid. 100 means that a motif must have occurrences in every sequences.

Total min length <number>

The minimal length of the whole motif, i.e. the sum of minimal lengths of each box. Warning: the length of the gaps between boxes mustn't me taken into account. The total minimal length may differ of the sum of boxs's minimal length: you can, for instance, infer motifs made of two boxes, with min length of boxes equals to 4 and a total min length equals to 10.

Total max length <number>

Same explanation as "Total min length", excepted that a 0 length means "infinity".

Total substitutions <number>

Total maximum number of substitutions for the whole motif. As for the total length, this is not necessarily the sum of each box's substitution number.

Boxes <number>

The number of boxes that compose the motifs to infer. When inferring simple one box motifs, it's not necessary to use local criteria as global and local criteria will be the same.

Composition in <symbol> <number> [OPTIONAL]

The number of a given symbol of the motif's alphabet may be restrained to a maximum by this criteria.

BOX <number>

Begin the description of the criteria of a given box of the motif.

Min length <number>

Minimum length for the current box.

Max length <number>

Same explanation as "Min length", excepted that a 0 length means "infinity".

Substitution <number>

Maximum number of substitutions allowed for the current box.

Composition in <symbol> <number> [OPTIONAL]

Same as the global composition, but for the current box.

Min spacer length <number>

Minimum number of symbols between the end of the current box and the beginning of the next one. This parameter mustn't appear in the last box's criteria, which has no next box!

Max spacer length <number>

Same explanation as "Max spacer length".

Delta <number> [OPTIONAL]

This criteria allows one to infer motifs composed of several boxes without really knowing the distance between these boxes. The min and max spacer length will be used as a "large" interval, and the delta's value will define the size of small intervals into this large one. An inference of two boxes motifs with a [10-20] range of distance between the boxes will produce motifs whose occurrences respect this range. A "Delta" criteria fixed to 2, for instance, will realize the same inference in all the possible ranges [i-delta, i+delta] (here: [10-14], [11-15], ...). As many output files as different ranges will be produced.

Palindrome of box <number> [OPTIONAL]

Indicate that the concerned box must be the biological palindrome of one of the previous boxes.

Shufflings <number> [OPTIONAL]

The number of shufflings of the original sequences to realize for the evaluation of the statistical significance of the motifs found.

Size k-mer <number> [OPTIONAL, always with shuffling]

Length of the words to conserve during shufflings (usually 2).

Against wrong sequences <filename> [OPTIONAL]

Another method to evaluate the significance of the motifs (not compatible with the shuffling method). In the case where you have a sequence file where you believe that the motifs you look for in the first sequences set won't appear, you can give to mlv-smile such a sequence file. The statistical evaluation of motifs found will be made by computing theit frequency in the "wrong sequences".

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