RSA-tools - oligo-analysis

Analysis of oligomer occurrences in nucleotidic of peptidic sequences

Reference: van Helden, J., André, B. and Collado-Vides, J. (1998). . J Mol Biol 281, 827-42.

Warning !! For vertebrate genomes, analyses of complete promoters from co-expressed gene groups return many false positive (i.e. if you submit a random set of genes, you always get plenty of highly 'significant' motifs). This is likely to come from the heterogeneity of human sequences (mixtures of GC-rich and GC-poor promoters).
However, analyses of ChIP-seq peaks return very good results. See the program peak-motifs.

Sequence       Format Paste your sequence in the box below

Or select a file to upload (.gz compressed files supported)


Mask 
Sequence type   
 purge sequences (highly recommended)
Oligomer counting mode
Oligomer length   prevent overlapping matches
Count on   return reverse complements together in the output
Background model 
Genome subset  Sequence type     


Estimate from input sequence
Markov model (higher order dependencies)  order  
Equiprobable residues (usually NOT recommended)

Custom background model
Upload your own background file     
    Format 

Pseudo-frequency  

Result

One row per pattern
Return fields Lower
Threshold 		Upper
Threshold
      E-value
      Significance
 Convert assembled patterns to matrices.
            Max matrices    Min site weight    Flanking residues
Occurrence table: one row per sequence, one column per oligo (occurrence counts only, email output recommended)

Pattern count distribubtions, one row per pattern (occurrence counts only, email output recommended)

Output