streme [options] p <primary sequences>
The name of a file containing the primary (positive) sequences in FASTA format. The file must contain at least two valid sequences or STREME will reject it. Note that the commandline version of STREME does not attempt to detect the alphabet from the primary sequences, so you should specify it with the dna, rna, protein or alph options.
STREME writes its output to files in a directory named
streme_out
, which it creates if necessary. You can change the
output directory using the o or oc options.
The directory will contain:
streme.html

an HTML file that provides the results in an interactive, humanreadable formatstreme.txt

a text file containing the motifs discovered by STREME in MEME formatsequences.tsv

a TSV (tabseparated values)sites.tsv

a TSV (tabseparated values)streme.xml

an XML file that provides the results in a format designed for machine processingSTREME gives each motif it discovers a name, which is a consensus sequence that approximately describes the motif, prefixed by a number from 1 to the number of motifs found, e.g., "1CCACYAGT". Motif names are intended to be mnemonic only, and are not intended to be used for searching sequences for matches; to search for matches to STREME motifs, use a STREME output file as input to a motif scanning program such as FIMO and MAST.
Note: All options may be preceded by a single dash () instead of a double dash () if desired.
Option  Parameter  Description  Default Behavior  

Output  
text  Just output the motifs discovered by STREME in MEME text format to standard output. No output directory is created.  The program behaves as if oc streme_out had
been specified. 

Objective Function  
objfun  de cd  This option is used to select the objective function that
STREME optimizes in searching for motifs.

STREME uses the Differential Enrichment (de) function.  
Primary Sequences  
Control Sequences, Background Model and Holdout Set  
n  control sequences  The name of a file containing control (negative) sequences in FASTA format. The control sequences must be in the same sequence alphabet as the primary sequences. If the average length of the control sequences is longer than that of the primary sequences, STREME trims the control sequences so that both sets have the same average length (unless you also specify option notrim).  If you do not provide control sequences, STREME creates them by shuffling a copy of each primary sequence, using a morder shuffle (see next option). Shuffling also preserves the positions of noncore (e.g., ambiguous) characters in each sequence to avoid artifacts.  
notrim  Do not trim the control sequences even if their average length exceeds that of the primary sequences.  The control sequences will be trimmed if their average length exceeds that of the primary sequences. This may enable STREME to use the (more accurate) Fisher test rather than the Binomial test.  
order  m  If you do not provide control sequences, STREME will do an
an morder shuffle of each primary sequence to
to create control sequences. This preserves the frequencies of words of
length m+1 in each shuffled sequence.
Unless you specify a background model file (see bfile, below),
STREME will also estimate an morder Markov background model
from the control sequences (or the primary sequences if you do not provide
control sequences). STREME uses the fastagetmarkov
program with a total pseudocount of 1 to create the Markov model.
m must be in the range [0,..,5].
 STREME uses m=2 (DNA and RNA), and m=0 (Protein and Custom alphabets).  
bfile  file  Specify the source of a background model in Markov Background Model Format. STREME uses the morder portion of the background model for loglikelihood scoring of motif sites, where m is as described for the order option, above.  STREME estimates an morder background model from the control sequences, or from the primary sequences if you do not provide control sequences.  
kmer  k  Deprecated: Use order instead. Preserve the frequencies of words (kmers) of this size when shuffling primary sequences to create control sequences. The value of k must be in the range [1,..,6]. STREME also estimates a background model of order k1 from the primary sequences for use in loglikelihood scoring of motif sites.  STREME preserves the frequencies of words of length 3 (DNA and RNA), and 1 (Protein and Custom alphabets), and constructs background models of order 2 (DNA and RNA), and order 0 (Protein and Custom).  
hofract  hofract  The fraction of the primary and control sequences that STREME will randomly select
and hold out for accurately estimating the significance of motifs.
Note: If the holdout set would contain fewer than 5 sequences, STREME does not create it, and the motif pvalues will be inaccurate. Note: The letter frequencies in the final motifs reported by STREME are based on all primary sequences, including those in the holdout set. 
STREME reserves 0.1 (10%) of the primary and control sequences for estimating the significance of motifs.  
totallength  len  Restrict the maximum total length of the sequences used by STREME from the sequence file(s) to a total of at most len. The input sequences are first sorted alphabetically by sequence content, and then their order is randomized. (Potential) sequences are then assigned to the primary and holdout sets. Then sequences are added in to the primary set in a the random order, skipping any potential sequence that would cause the total length of the primary set to exceed len times (1  hofract). This is repeated for the holdout set, not adding a sequence if the total length of the holdout set would exceed len times hofract.  The total length of the input sequences is not limited.  
seed  seed  Random seed for shuffling and sampling the holdout set sequences (see above).  STREME uses a random seed of 0.  
Alphabet  
Number of Motifs  
thresh  thresh  STREME will stop searching for motifs when too many consecutive motifs have pvalues greater than thresh (or Evalues greater than thresh if you specify option evalue, below). For the definition of "too many", see option patience, below.  0.05  
evalue  Stop searching for motifs based on their Evalues.  Stop searching for motifs based on their pvalues.  
patience  patience  Stop searching for motifs when patience consecutive nonsignificant motifs have been found. (Can be overridden by the nmotifs or time options; see below.)  3  
nmotifs  nmotifs  STREME will stop searching for motifs after finding nmotifs motifs.  STREME stops when too many consecutive, nonsignificant motifs have been found.  
time  secs  STREME will stop searching for motifs if it has found at least one motif and it estimates that finding any more will cause the total running time to exceed secs seconds.  STREME stops when too many consecutive, nonsignificant motifs have been found.  
Motif Width  
minw  minw  Search for motifs with a width ≥ minw.  Searches for motifs with a minimum width of 8.  
maxw  maxw  Search for motifs with a width ≤ maxw.  Searches for motifs with a maximum width of 15.  
w  w  Search for motifs with a width of w. Overrides minw and maxw.  See minw and maxw, above.  
Seed Evaluation and Refinement  
neval  neval  The number of seed words of each width from 3 to maxw to evaluate for enrichment of approximate matches.  25  
nref  nref  The number of seed words of each width from minw to maxw to convert to motifs and optimize using an iterative refinement algorithm.  4  
niter  niter  The iterative refinement algorithm is run for niter iterations, or until convergence, which ever comes first.  20  
Misc  
align  left  center  right  For the site positional distribution diagrams, align the sequences on their left ends (left), on their centers (center), or on their right ends (right). For visualizing motif distributions, center alignment is ideal for ChIPseq and similar data; right alignment for sequences upstream of transcription start sites; left alignment for many proteins or 3' UTR sequences.  Align the sequences on their centers.  
verbosity  12345  A number that regulates the verbosity level of the output information messages. If set to 1 (quiet) then STREME will only output warning and error messages, whereas the other extreme 5 (dump) outputs lots of information intended for debugging.  The verbosity level is set to 2 (normal). 
STREME searches for motifs by iterating the following five steps to until the selected stopping criterion is met. The stopping criteria are described in the "Number of Motifs" section, above.
STREME builds a generalized suffix tree that includes both the primary and control sequences (but not the holdout set sequences). If the alphabet is complementable, STREME adds the reverse complement of each primary and control sequence to the tree as well. For the first round of STREME, the input sequences are used to build the tree. For subsequent rounds, the sequences from the last step (Step 5, below), with previous motifs erased, are used.
For each word of length 3 to the maximum motif width in the primary sequences,
STREME uses the tree to efficiently count the numbers of exact matches
to the word in the primary and control sequences,
and computes its enrichment pvalue using the chosen objective function.
For each of the neval
(default=25) most signficant words of each width,
STREME then uses the tree to count the number of approximate matches
to it, and computes its enrichment pvalue.
(Note: With the Differential Enrichment objective function,
STREME will use the Binomial test instead of Fisher's exact test
if the primary and control sequences have different average
lengths. With the Central Distance objective function,
STREME computes the cumulative Bates distribution of the average distances of
the seed word from the centers of the sequences.)
For each word of length 3 to the maximum motif width in the primary sequences,
STREME uses the tree to efficiently count the numbers of exact matches
to the word in the primary and control sequences,
and computes its enrichment pvalue using the chosen objective function.
For each of the neval
(default=25) most signficant words of each width,
STREME then uses the tree to count the number of approximate matches
to it, and computes its enrichment pvalue.
STREME converts each of the nref
(default=4) most significant
seed words into a motif, and iteratively refines each motif, selecting the motif that
best discriminates the primary sequences from the control sequences.
At each iteration of refinement, the current motif and the (k1)order
background are used with the suffix tree to efficiently find the best
site in each sequence. The primary and control sequences are then sorted
by the loglikelihood score of their best site, and the score threshold
that optimizes the pvalue of the statistical test
(which depends on the chosen objective function) is found.
The iteration ends by estimating a new version of the motif
from the single best site in each primary sequence whose
score is above the optimal threshold. This new motif is
used in the next refinement iteration. Refinement stops
when the pvalue fails to improve, or when
niter
(default=20) iterations have been performed.
STREME computes the statistical significance of the of the motif by using the motif and the optimal discriminative score threshold (based on the primary and control sequences) to classify the holdout set sequences, and then applying the statistical test (Fisher's exact test, Binomial test, or the cumulative Bates distribution) to the classification. Classification is based on the best match to the motif in each sequence (on either strand when the alphabet is complementable). If the primary or control holdout set would contain fewer than 5 sequences, STREME does not create a holdout set, and the value of the statistical test will not be an accurate measure of the statistical significance of the motif. In that case STREME will label the test output as a 'score' rather than as a pvalue. If there is a holdout set, STREME also reports an Evalue that accounts for the number of motifs tested by STREME. The Evalue is the pvalue multiplied by the number of motifs reported by STREME, and is an estimate of how many equally enriched (or better) motifs would be found in shuffled versions of the primary sequences.
STREME "erases" each of the sites of the best motif from both the primary and control sequences by converting the sites to the separator character. Only the positions in the site where the letter has a positive likelihood ratio are erased to allow some overlap of sites of different motifs.
The running time and memory usage of STREME depends on the total size of the sequences in its input, the length of the sequences, the alphabet of the sequences and the minimum and maximum motif widths. The following tables show the running times and memory usage for STREME on on different size datasets (of random sequences), as a function of the length of the sequences, on a 3.2 GHz Intel Core i7 processor with 16GB of memory. STREME was run using a single thread, and the motif width was the maximum allowed range: minimum = 5, maximum = 30. The total sizes of the sequences in the datasets from 100,000 (1 x 10^{5}) to 20,000,000 (2 x 10^{7}).
With very short sequences (length = 5), STREME is extremely fast, processing 4,000,000 DNA sequences in less than 100 seconds. The running time increases with sequence length, reaching a maximum for sequences around 30 long. With very long sequences, STREME is runs more quickly, with length 10,000 sequences taking approximately the same time per motif discovered as length 10 sequences. STREME runs about twice as slow on DNA sequences as on RNA sequences because STREME treats DNA sequences as doublestranded and RNA sequences as singlestranded. Because of the larger alphabet size, STREME runs about 5 times more slowly on protein sequences than on RNA sequences, which is the same factor as the ratio of the alphabet sizes (20/4). The running time of STREME with sequences over a custom alphabet will similarly be (roughly) proportional to the number of letters in the custom alphabet.
STREME Running Time (seconds / motif)  

DNA  RNA  Protein 
STREME Virtual Memory Size (bytes)  
DNA  RNA  Protein 