What is e value in MEME?

E-value: The E-value of the match of a sequence in a database to a group of motifs is defined as the expected number of sequences in a random database of the same size that would match the motifs as well as the sequence does and is equal to the combined p-value of the sequence times the number of sequences in the …

How does MEME motif work?

A motif is an approximate sequence pattern that occurs repeatedly in a group of related sequences. MEME represents motifs as position-dependent letter-probability matrices that describe the probability of each possible letter at each position in the pattern. Individual MEME motifs do not contain gaps.

How long is the motif produced by meme?

The motifs are typically compendia of DNA- or RNA-binding motifs, and the sequences might be: 500 bp sequences aligned on ChIP-seq peaks or summits; 300 bp sequences centered on sets of transcription start sites or translation start sites; sequences aligned on splice-junctions; etc.

Which is the best format for MEME motif?

The MEME Minimal Motif Format is a simple text format for motifs that is accepted by the programs in the MEME Suite that require MEME Motif Format.

What is a motif in the MEME suite?

MEME discovers novel, ungapped motifs (recurring, fixed-length patterns) in your sequences (sample output from sequences). MEME splits variable-length patterns into two or more separate motifs. See this Manual for more information. A motif is an approximate sequence pattern that occurs repeatedly in a group of related sequences.

How is the MEME suite used in sequence analysis?

***Introduction*** The MEME suite provides online tools for discovering and using protein and DNA sequence motifs. A motif is a pattern of nucleotides or amino acids that appears repeatedly in a group of related DNA or protein sequences. The MEME suite represents motifs as position-dependent scoring matrices.

When to use the non overlapping motif option in meme?

MEME assumes each sequence may contain any number of non-overlapping occurrences of each motif. This option is useful when you suspect that motifs repeat multiple times within a single sequence. In that case, the motifs found will be much more accurate than using one of the other options.