Click on the menu at the left to see which of the following motif input methods are available.
Type in motifs
When this option is available you may directly input multiple motifs
by typing them (or using "cut-and-paste").
First select the desired motif alphabet using the menu
immediately to the left. If you select the "Custom" option then
you must provide an alphabet definition
in the file input that immediately follows. Warning: custom alphabets are case-sensitive.
You may optionally give each motif an identifier and alternate name by
inputting a line like >Identifer Alternate-Name preceeding the motif.
You can then enter each motif as either matrices, sequence sites or regular expressions.
You can enter multiple motifs by typing an empty line after each motif.
Individual motifs will be shown in square brackets, and errors in your
motifs will be highlighted in red while warnings will be highlighted in
yellow.
Mouse-over individual motifs to display their sequence logos.
View the examples for more information on what is possible.
Upload motifs
When this option is available you may upload a file containing
motifs in MEME motif format. This includes the outputs generated by MEME
and DREME, as well as files you create using the
motif conversion scripts
or manually following the
MEME motif format guidelines.
Databases (select category)
When this option is available you can select the category of
motif database desired from the list below it. Then select the motif
database from the displayed list.
Consult the
motif database documentation
for descriptions of all the motif databases present on this MEME Suite server.
Submitted motifs
This option is only available when you have invoked the current
program by clicking on a button in the output report of a different MEME Suite program.
By selecting this option you will input the motifs sent by that program.
You may input both probability and count matrices of either orientation
and the rules described below will be used to convert the matrix into a
MEME formatted motif.
Alphabet Order
The counts/probabilities are expected to be ordered based on the
alphabetical ordering of their codes. So DNA is ordered ACGT and
protein is ordered ACDEFGHIKLMNPQRSTVWY. For custom alphabets the ordering
goes uppercase letters (A-Z), lowercase letters (a-z), numbers (0-9) and
finally the symbols '*', '-' and '.'.
Matrix Orientation
Matrix motifs may be input with either one position per row (preferred)
which is called row orientation, or one position per column which is
called column orientation. The orientation is determined by picking
which dimension (row or column) is equal to the alphabet size. If both
dimensions are equal to the alphabet size then row orientation is assumed.
If neither dimension is equal to the alphabet size then the closest
that is still smaller than the alphabet size is picked, however if both
are equally smaller then column orientation is assumed. Finally if none of
the above rules work to determine the orientation then row orientation is
assumed.
Site counts
Once the orientation is determined, the sum of the numbers that make up
the first position is calculated and rounded to the nearest integer.
If that value is larger than 1 then the matrix is assumed to be a count
matrix and that value is used as the site count, otherwise the matrix is
assumed to be a probability matrix and a site count of 20 is used.
Converting to a normalized probability matrix
Once the orientation is determined then each number in the matrix is
converted to a normalized probability by dividing by the sum of all the
numbers for that motif position. If any numbers are missing they are
assumed to have the value zero. As a special case if all numbers in a
motif position have the value zero then they are given the uniform
probability of 1 / alphabet size.
Yellow highlighting and red annotations
Red asterisks (*) indicate where the
parser thinks values are missing. A yellow highlighted row or column
with a red number at the end indicates that the counts for that position
don't sum to the same count as the first position. The red number shows
the difference. If the red number is negative then that position sums to
less then the first position, if it is positive then it sums to more than
the first position.
Typed Motifs - Sequence Sites or Regular Expressions
You may input one or more sites of the motif including using ambiguity
codes or bracket expressions to represent multiple possibilities for a
single motif position.
Ambiguity Codes
The DNA and protein alphabets include additional codes that represent
multiple possible bases. For example the DNA alphabet includes W (for weak)
which represents that the given position could be either a A (for adenosine)
or a T (for thymidine).
Bracket Expressions
Bracket expressions also group together multiple codes so they share
a single position. Their syntax is a opening square bracket '[' followed
by one or more codes and a closing square bracket ']'. For example with a
DNA motif the bracket expression [AT] means that both A and T are
acceptable and is equivalent to the ambiguity code W. Any repeats of a
base in a bracket expression are ignored so for example a DNA bracket
expression [AAT] has the same effect as [AT] or [AW] or W.
Multiple sites
When only one site is provided the site count is set to 20, however
you can precisely control the motif by providing multiple sites. Each of
these sites can still contain ambiguity codes and bracket expressions
but a single count will be divided among the selected bases for each
position. When multiple sites are provided the site count will be set
to the number of sites provided.
DNA motifs support the standard 4 codes for the bases: adenosine (A),
cytidine (C), guanosine (G) and thymidine (T) as well as supporting
the following ambiguity codes.
When enabled this field supports selecting motifs from the file with a
space separated list of motif identifiers and/or their positions in the
file.
Any numbers in the range 1 to 999 are assumed to refer to the position
of the selected motif in the file, so the entry "3" always refers to the
third motif. Any other entry is assumed to be a motif identifier.
Motif identifiers can not start with a dash and can only contain
alphanumeric characters as well as colon ':', underscore '_', dot '.'
and dash '-'.
This option can help change the alphabet of motifs from
a base alphabet to a derived alphabet.
This might be useful if you need to compare an extended DNA motif with
a library of DNA motifs, or if you wish to compare RNA motifs to DNA motifs.
Note that this option will also let you do nonsensical things like compare
Protein motifs to DNA motifs so use it with care.
The derived alphabet must have all the core symbols of the alphabet
that it is derived from. For example if the alphabet is derived from DNA
it must have ACGT as core symbols. Expanding the alphabet adds frequencies
of zero for every symbol in the derived alphabet that did not exist in the
base alphabet.
Click on the menu at the left to see which of the following sequence input methods are available.
Type in sequences
When this option is available you may directly input multiple
sequences by typing them. Sequences must be input in
FASTA format.
Upload sequences
When this option is available you may upload a file containing
sequences in FASTA format.
Upload BED file
When this option is available you may upload a file containing
sequence coordinates in BED format.
Databases (select category)
When this option is available you may first select a category of
sequence database from the list below it. Two additional menus will then appear
where you can select the particular database and version desired, respectively.
The full list of available sequence databases and their descriptions
can be viewed HERE.
Submitted sequences
This option is only available when you have invoked the current
program by clicking on a button in the output report of a different MEME Suite program.
By selecting this option you will input the sequences sent by that program.
Specify a file to upload containing
sequence coordinates in BED format.
The file must be based on the exact genome version you specified in the
menus above.
Selecting this option will filter the sequence menu to only contain
databases that have additional information that is specific to a tissue
or cell line.
This option causes MEME Suite to use tissue/cell-specific information
(typically from DNase I or histone modification ChIP-seq data) encoded
as a position specific prior that
has been created by the MEME Suite create-priors
utility. You can see a description of the sequence databases
for which we provide tissue/cell-specific priors
here.
Note that you cannot upload or type in your own sequences
when tissue/cell-specific scanning is selected.
Enter the email address where you want the job notification email to
be sent. Please check that this is a valid email address!
The notification email will include a link to your job results.
Note: You can also access your jobs via the Recent Jobs
menu on the left of all MEME Suite input pages. That menu only
keeps track of jobs submitted during the current session of your internet browser.
Note: Most MEME Suite servers only store results for a couple of days.
So be sure to download any results you wish to keep.
You provide one set of sequences MEME-ChIP reports motifs enriched
in this set.
MEME discovers motifs enriched relative to a random model based on
frequencies of the letters in your sequences, or relative to the frequencies
given in a "background model" that you may provide (see "Universal options").
STREME discovers motifs that are enriched in your sequences relative
to a control set of sequences that STREME creates by shuffling each of your sequences,
conserving dinucleotide frequencies.
CentriMo identifies motifs enriched in a central (or uncentered, see "CentriMo options")
region relative to the flanking regions.
Discriminative mode
You provide two sets of sequences and MEME-ChIP reports motifs that
are enriched in the first (primary) set relative to the second (control) set.
MEME motifs use the classic MEME objective function with a position-specific prior
created from the primary and control sequences using using psp-gen.
Note:The sequences in the primary and control sets should all be the same length.
Differential Enrichment mode
You provide two sets of sequences and MEME-ChIP discovers motifs that
are enriched in the first (primary) set relative to the second (control) set.
In Differential Enrichment mode, MEME motifs are discovered using an objective function based on the
hypergeometric distribution to determine the relative enrichment of sites in the
primary sequences compared to the control sequences.
The primary sequences should all be the same length.
The recommended length for ChIP-seq sequences is 500 bp
centered on the summit (or center if the summit is not known) of a peak.
MEME-ChIP works best with sequences no longer than 2000 bp.
There may be at most 500,000 (primary) sequences
in FASTA format. There is also
a limit of 80,000,000 bytes for the entire contents of the input form.
MEME-ChIP can analyze peak regions identified by ChIP-seq,
cross-linking sites identified by CLIP-seq and related assays,
as well as sets of genomic regions selected using other criteria (e.g., TSSs of
differentially expressed or bound genes).
The control sequences should all be the same length as the primary sequences.
The recommended length for ChIP-seq sequences is 500 bp
centered on the summit (or center if the summit is not known) of a peak.
MEME-ChIP works best with sequences no longer than 2000 bp.
There may be at most 500,000 control sequences
in FASTA format. There is also
a limit of 80,000,000 bytes for the entire contents of the input form.
If the primary sequences are ChIP-seq peak regions from a
transcription factor ChIP-seq experiment, similar regions
from a knockout cell line or organism, are a possible choice
for control sequences. The control sequences should be prepared
in exactly the same way (e.g., repeat-masking) as the primary sequences.
When this option is selected, if the FASTA sequence header of an input
sequence contains genomic coordinates in UCSC or Galaxy format the discovered motif sites
will be output in genomic coordinates. If the sequence header does
not contain valid coordinates, the sites will be output with
the start of the sequences as position 1.
MEME-ChIP will use this set of motifs for motif enrichment analysis
and will also report if any motifs that it discovers in your sequences
are similar to any motifs in this set.
This is the width (number of letters in the sequence pattern) of a
single motif. MEME and STREME choose the optimal width of each motif individually
using a statistical heuristic function. You can choose different limits
for the minimum and maximum motif widths that MEME and STREME will consider. The
width of each motif that MEME and STREME report will lie within the limits you
choose.
The background model normalizes for biased distribution of
letters and groups of letters in your sequences.
A 0-order model adjusts for single letter biases, a 1-order model adjusts for
dimer biases (e.g., GC content in DNA sequences), etc.
By default MEME-ChIP will determine the background Markov model from
the primary sequences (or from the control sequences if you provide them).
You may select a Markov model order of 0 to 4.
Alternately you may select "Upload background model" and input a file containing
a background model.
The downloadable version of the MEME Suite contains a program named
"fasta-get-markov" that you can use to create background model files in
the correct format from FASTA sequence files.
This is where you tell MEME how you believe occurrences of the motifs
are distributed among the sequences. Selecting the correct type of
distribution improves the sensitivity and quality of the motif search.
Zero or one occurrence per sequence
MEME assumes that each sequence may contain at most one
occurrence of each motif. This option is useful when you suspect that
some motifs may be missing from some of the sequences. In that case, the
motifs found will be more accurate than using the one occurrence per
sequence option. This option takes more computer time than the one
occurrence per sequence option (about twice as much) and is slightly less
sensitive to weak motifs present in all of the sequences.
One occurrence per sequence
MEME assumes that each sequence in the dataset contains
exactly one occurrence of each motif. This option is the fastest
and most sensitive but the motifs returned by MEME may be "blurry" if
any of the sequences is missing them.
Any number of repetitions
MEME assumes each sequence may contain any number of
non-overlapping occurrences of each motif. This option is useful when
you suspect that motifs repeat multiple times within a single sequence.
In that case, the motifs found will be much more accurate than using one
of the other options. This option can also be used to discover repeats
within a single sequence. This option takes much more computer time than
the one occurrence per sequence option (about ten times as much) and is
somewhat less sensitive to weak motifs which do not repeat within a
single sequence than the other two options.
MEME will keep searching until it finds this many motifs or it hits
some other threshold like the maximum run time. Note that MEME does not
use an p-value threhold like STREME, so you should always check the E-value
of any found motifs.
This is the total number of sites in the training set where a single
motif occurs. You can choose different limits for the minimum and maximum
number of occurrences that MEME will consider. If you have prior knowledge
about the number of occurrences that motifs have in your training set,
limiting MEME's search in this way can can increase the likelihood of
MEME finding true motifs.
MEME chooses the number of occurrences to report for each motif by
optimizing a statistical heuristic function, restricting the number of
occurrences to the range you give here, or using defaults described below
if you leave these fields deselected.
Checking this box causes MEME to search only for DNA palindromes. This
causes MEME to average the letter frequencies in corresponding motif
columns together. For instance, if the width of the motif is 10, columns
1 and 10, 2 and 9, 3 and 8, etc., are averaged together. The averaging
combines the frequency of A in one column with T in the other, and the
frequency of C in one column with G in the other. If this box is not
checked, the columns are not averaged together.
If your (primary) sequences are sorted in order of confidence (best to worst)
then you should select this option. This will cause MEME not to randomize
the the order of the (primary) sequences before sampling starting points if
there are more than 1000 sequences. See the
MEME documentation
for the -norand option for more details.
For the STREME site positional distribution diagrams, align the sequences
on their left ends, on their centers, or on their right ends.
For visualizing motif distributions, center alignment is
ideal for ChIP-seq and similar data; right alignment
for sequences upstream of transcription start sites; left
alignment for many proteins or 3' UTR sequences.
Specify a minimum score for a match to be considered. If a sequence does
not have any matches which meet this minimum score for a given motif, then
that sequence will not be considered for that motif.
This option limits the maximum region size that CentriMo will test.
This option is useful if your sequences are quite long (> 500 bp) or
you are interested only in narrow regions of enrichment.
Limiting the size of the maximum region reduces the impact of the
multiple testing correction, increasing the sensitivity of the analysis.
When this option is not supplied CentriMo will test region sizes up to
one less than the maximum number of places that a given motif can align to
the sequence.
This is the E-value threshold CentriMo uses for reporting enriched
central regions for motifs. If multiple enriched regions overlap then the region
with the best p-value and smallest size will be output.
This option causes all regions up to the maximum region size to be
considered even if they are not in the center. This can be useful when
your sequences are aligned on a genomic landmark (e.g., TSS) since
a motif might be enriched at a particular distance upstream or downstream
of the landmark.
This option causes CentriMo to store the identifiers (IDs) of sequences
that have their best match in the most enriched region for each motif. This will
allow you to easily extract the IDs of the sequences contributing to
the enrichment of one or more motifs in the CentriMo output. This option
makes the CentriMo output file much larger.
