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 negative.fasta
  
  Database contains 98 sequences, 9800 residues

  MOTIFS meme_out/meme.txt (DNA)
  
        MOTIF
        WIDTH
        
         BEST POSSIBLE MATCH
        
        MTTYYCYYTCYTCCT
        15
        ATTCTCTCTCTTCCT
       
        SGTKKTTWRKASTTWTWTGSGWMAKAARGAGRARAYW
        37
        GGTTTTTAGTAGTTTTTTGCGACATAAGGAGAAAACA
       
        AAAGTRAGGGG
        11
        AAAGTGAGGGG
       
Random model letter frequencies (--nrdb--):

A 0.282 C 0.222 G 0.229 T 0.267

MOTIF	WIDTH	BEST POSSIBLE MATCH
MTTYYCYYTCYTCCT	15	ATTCTCTCTCTTCCT
SGTKKTTWRKASTTWTWTGSGWMAKAARGAGRARAYW	37	GGTTTTTAGTAGTTTTTTGCGACATAAGGAGAAAACA
AAAGTRAGGGG	11	AAAGTGAGGGG

SECTION I: HIGH-SCORING MOTIF OCCURENCES

There were 10 motif occurences with a p-value less than 0.001. 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
MTTYYCYYTCYTCCT	MEME-1	1055430	+	42	56	1.38e-05	0.114	ATTGCCATTCTTCTT
MTTYYCYYTCYTCCT	MEME-1	204151	+	15	29	2.78e-05	0.115	TTTTTTGTGCCTCCT
MTTYYCYYTCYTCCT	MEME-1	189063	+	42	56	8.19e-05	0.225	CTTGCCGTGCATCTT
MTTYYCYYTCYTCCT	MEME-1	826841	+	29	43	0.000128	0.265	ATTTCTGTGTTCCCT
MTTYYCYYTCYTCCT	MEME-1	826841	+	46	60	0.000621	0.781	AGTGTTTCGACTCCC
MTTYYCYYTCYTCCT	MEME-1	1017814	+	25	39	0.000685	0.781	GCTCCCTGTCTTGCT
MTTYYCYYTCYTCCT	MEME-1	575836	+	63	77	0.000744	0.781	CGTCCCGTCCTCCGT
MTTYYCYYTCYTCCT	MEME-1	1078052	+	25	39	0.000808	0.781	TGTCATGCTCCCCCA
MTTYYCYYTCYTCCT	MEME-1	1105801	+	71	85	0.000888	0.781	GTTCTCTTGATTCTT
MTTYYCYYTCYTCCT	MEME-1	566750	+	79	93	0.000948	0.781	CGTGTCTCCCCCCAT

DEBUGGING INFORMATION

Command line:

fimo --norc -motif MTTYYCYYTCYTCCT -thresh 0.001 meme_out/meme.txt negative.fasta

Settings:


  
    output_directory = fimo_out
    MEME file name = meme_out/meme.txt
    sequence file name = negative.fasta
  
  
    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 = false
    max strand = false
  
  
    threshold type = p-value
    output theshold = 0.001
    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_out/meme.txt	sequence file name = negative.fasta
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 = false	max strand = false
threshold type = p-value	output theshold = 0.001	pseudocount = 0.1
alpha = 1	verbosity = 2