FIMO Results

Database and Motifs

High-scoring Motif Occurences

Debugging Information

Results in TSV Format

Results in GFF3 Format

FIMO - Motif search tool

FIMO version 5.5.1, (Release date: Sun Jan 29 10:33:12 2023 -0800)

For further information on how to interpret these results please access https://meme-suite.org/meme/doc/fimo-output-format.html.
To get a copy of the FIMO software please access https://meme-suite.org

If you use FIMO in your research, please cite the following paper:
Charles E. Grant, Timothy L. Bailey, and William Stafford Noble, "FIMO: Scanning for occurrences of a given motif", Bioinformatics, 27(7):1017-1018, 2011. [full text]

DATABASE AND MOTIFS

  DATABASE try.fa
  
  Database contains 200 sequences, 20000 residues

  MOTIFS meme.txt (DNA)
  
        MOTIF
        WIDTH
        
         BEST POSSIBLE MATCH
        
        KWSKYCVMWGGTTCGAATCCKTCABSVCSCACCACTTTWYT
        41
        GTGGTCGAAGGTTCGAATCCTTCACGGCCCACCACTTTATT
       
        GAAAGTGCATAAATCAGCGCAAYACC
        26
        GAAAGTGCATAAATCAGCGCAACACC
       
        TAGRGCAGTTGGCTTTTAACC
        21
        TAGAGCAGTTGGCTTTTAACC
       
Random model letter frequencies (--nrdb--):

A 0.275 C 0.225 G 0.225 T 0.275

MOTIF	WIDTH	BEST POSSIBLE MATCH
KWSKYCVMWGGTTCGAATCCKTCABSVCSCACCACTTTWYT	41	GTGGTCGAAGGTTCGAATCCTTCACGGCCCACCACTTTATT
GAAAGTGCATAAATCAGCGCAAYACC	26	GAAAGTGCATAAATCAGCGCAACACC
TAGRGCAGTTGGCTTTTAACC	21	TAGAGCAGTTGGCTTTTAACC

SECTION I: HIGH-SCORING MOTIF OCCURENCES

There were 7 motif occurences with a p-value less than 0.0001. The full set of motif occurences can be seen in the TSV (tab-delimited values) output file fimo.tsv, the GFF3 file fimo.gff which may be suitable for uploading to the UCSC Genome Table Browser (assuming the FASTA input sequences included genomic coordinates in UCSC or Galaxy format), or the XML file fimo.xml.
The p-value of a motif occurrence is defined as the probability of a random sequence of the same length as the motif matching that position of the sequence with as good or better a score.
The score for the match of a position in a sequence to a motif is computed by summing the appropriate entries from each column of the position-dependent scoring matrix that represents the motif.
The q-value of a motif occurrence is defined as the false discovery rate if the occurrence is accepted as significant.
The table is sorted by increasing p-value.

Motif ID	Alt ID	Sequence Name	Strand	Start	End	p-value	q-value	Matched Sequence
KWSKYCVMWGGTTCGAATCCKTCABSVCSCACCACTTTWYT	MEME-1	187	+	20	60	8.57e-06	0.206	TATGTCATTAGTGTTATTACTGTTTGCGGTAACGGCTTTGG
TAGRGCAGTTGGCTTTTAACC	MEME-3	148	+	65	85	1.18e-05	0.376	TTTCGCAGTTGGCCTTTAACT
GAAAGTGCATAAATCAGCGCAAYACC	MEME-2	160	-	48	73	1.8e-05	0.322	GAGGTGGCAGAATCTACCGTAATACC
GAAAGTGCATAAATCAGCGCAAYACC	MEME-2	153	+	39	64	2.15e-05	0.322	GAGTCTGCCTAAGTAAGGGCAGCGCC
KWSKYCVMWGGTTCGAATCCKTCABSVCSCACCACTTTWYT	MEME-1	16	+	53	93	3.12e-05	0.375	CTGTATCTGGGCTGGGACCCGCTCGGATCCAACAATTATTA
TAGRGCAGTTGGCTTTTAACC	MEME-3	46	+	62	82	7.72e-05	1	AAAAGCGGTACACTTGTAAGC
GAAAGTGCATAAATCAGCGCAAYACC	MEME-2	154	+	3	28	9.56e-05	0.954	AAATGAGCAAAATTTCGTGCATTTGC

DEBUGGING INFORMATION

Command line:

fimo meme.txt try.fa

Settings:


  
    output_directory = fimo_out
    MEME file name = meme.txt
    sequence file name = try.fa
  
  
    background file name = --nrdb--
    alphabet = DNA
    max stored scores = 100000
  
  
    allow clobber = true
    compute q-values = true
    parse genomic coord. = false
  
  
    text only = false
    scan both strands = true
    max strand = false
  
  
    threshold type = p-value
    output theshold = 0.0001
    pseudocount = 0.1
  
  
    alpha = 1
    verbosity = 2

This information can be useful in the event you wish to report a problem with the FIMO software.

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output_directory = fimo_out	MEME file name = meme.txt	sequence file name = try.fa
background file name = --nrdb--	alphabet = DNA	max stored scores = 100000
allow clobber = true	compute q-values = true	parse genomic coord. = false
text only = false	scan both strands = true	max strand = false
threshold type = p-value	output theshold = 0.0001	pseudocount = 0.1
alpha = 1	verbosity = 2