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Sequence Analysis of Motifs Enrichment

Sequence Analysis of Motifs Enrichment

This module computes a discriminative motif enrichment analysis. To run the software locally, you should agree to the terms of the Academic License Agreement, which can be found here.



 

Submission reference: 127917


Submission label (optional)



Email address (optional)
We suggest to provide an email address for jobs that contain more than 500 sequences



Reference set

Shuffle
Random
Custom


Set Coverage
Default is recommended for majority of users and provides simplicity and robustness. Switching to a lower threshold might yield to a different result but at potential cost of increased computational time. A higher threshold can speed up calculation but is only recommended using high quality data (e.g. iCLIP).

60%
65%
75% (default)
80%
85%
90%
95%


Use only given strand

True
False


Filter motif redundancy

True
False


Upload a Positive dataset (FASTA format, at least 10 and at most 104 sequences)


Upload a Reference dataset (FASTA format, at least 10 and at most 104 sequences)




Submission status:



Sample data

Just trying it out? Pre-populate the form with: (Please, check that you do not have active proxies!)

PAR-CLIP bound/unbound transcripts (FUS protein) - Hoell. et al., 2011