FIMO Results

FIMO - Motif search tool

FIMO version 5.5.5, (Release date: Thu Sep 14 08:48:04 2023 +1000)

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 MOA1_gain_diff.fa
  
  Database contains 751 sequences, 18143 residues

  MOTIFS streme_out/streme.xml (DNA)
  
        MOTIF
        WIDTH
        
         BEST POSSIBLE MATCH
        
        1-CAGGAAGT
        8
        CAGGAAGT
       
        2-CASCAG
        6
        CAGCAG
       
        3-TGASTCA
        7
        TGAGTCA
       
        4-TCAGCA
        6
        TCAGCA
       
        5-CAGAGGS
        7
        CAGAGGC
       
Random model letter frequencies (./background):

A 0.260 C 0.240 G 0.240 T 0.260

MOTIF	WIDTH	BEST POSSIBLE MATCH
1-CAGGAAGT	8	CAGGAAGT
2-CASCAG	6	CAGCAG
3-TGASTCA	7	TGAGTCA
4-TCAGCA	6	TCAGCA
5-CAGAGGS	7	CAGAGGC

SECTION I: HIGH-SCORING MOTIF OCCURENCES

There were 10 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
5-CAGAGGS	STREME-5	chr19	-	3126158	3126164	5.41e-05	0.145	CAGAGGC
5-CAGAGGS	STREME-5	chr11	-	6282184	6282190	5.41e-05	0.145	CAGAGGC
5-CAGAGGS	STREME-5	chr2	+	23404028	23404034	5.41e-05	0.145	CAGAGGC
5-CAGAGGS	STREME-5	chr1	-	48530946	48530952	5.41e-05	0.145	CAGAGGC
5-CAGAGGS	STREME-5	chrX	-	51168843	51168849	5.41e-05	0.145	CAGAGGC
5-CAGAGGS	STREME-5	chr17	+	61159658	61159664	5.41e-05	0.145	CAGAGGC
5-CAGAGGS	STREME-5	chr11	-	75774486	75774492	5.41e-05	0.145	CAGAGGC
5-CAGAGGS	STREME-5	chr2	+	96206107	96206113	5.41e-05	0.145	CAGAGGC
5-CAGAGGS	STREME-5	chr8	-	122447611	122447617	5.41e-05	0.145	CAGAGGC
5-CAGAGGS	STREME-5	chr3	+	192888318	192888324	5.41e-05	0.145	CAGAGGC

DEBUGGING INFORMATION

Command line:

fimo --verbosity 1 --oc fimo_out_2 --bgfile ./background --motif 5-CAGAGGS streme_out/streme.xml MOA1_gain_diff.fa

Settings:


  
    output_directory = fimo_out_2
    MEME file name = streme_out/streme.xml
    sequence file name = MOA1_gain_diff.fa
  
  
    background file name = ./background
    alphabet = DNA
    max stored scores = 100000
  
  
    allow clobber = true
    compute q-values = true
    parse genomic coord. = true
  
  
    text only = false
    scan both strands = true
    max strand = false
  
  
    threshold type = p-value
    output theshold = 0.0001
    pseudocount = 0.1
  
  
    alpha = 1
    verbosity = 1

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_2	MEME file name = streme_out/streme.xml	sequence file name = MOA1_gain_diff.fa
background file name = ./background	alphabet = DNA	max stored scores = 100000
allow clobber = true	compute q-values = true	parse genomic coord. = true
text only = false	scan both strands = true	max strand = false
threshold type = p-value	output theshold = 0.0001	pseudocount = 0.1
alpha = 1	verbosity = 1