{% extends "layout.html" %} {% block body %}

Motifs | Sequences | Other outputs | References | Runtime | Glossary

{% for motif, image_url, eps_url in motifs %}

Motif {{ motif.idx }}

log10 E-value = {{ '%.2f' % (motif.log_E_value / 2.3025850929940459) }}
Motif built from {{ motif.num_sites }} sites.
Motif predicts {{ motif.predictions.__len__() }} sites in {{ num_bases }} bases from {{ num_sequences }} input sequences {% if motif.input_stats.count %} ({{ '%.0f' % (motif.input_stats.num_bases / motif.input_stats.count) }} bp/site) {% endif %} .
{% if bg_num_bases %} Motif predicts {{ motif.bg_stats.count }} sites in {{ bg_num_bases }} bases from {{ bg_num_sequences }} background sequences {% if motif.bg_stats.count %} ({{ '%.0f' % (motif.bg_stats.num_bases / motif.bg_stats.count) }} bp/site) {% endif %} .
{% if not motif.bg_stats.count %} The input has an infinite enrichment of predictions over the background.
{% else %} The input has a {{ '%.1f' % calc_rel_enrichment(num_bases, bg_num_bases, motif) }}-fold enrichment of predictions per base over the background.
{% endif %} {% endif %} Logo image is missing!
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{% endfor %}


Sequences

Read {{ num_bases }} bases from {{ num_sequences }} input sequences. {{ '%.1f%%' % (unknown * 100) }} of bases were unknown. Other bases were distributed as: {% if bg_num_bases %}

Read {{ bg_num_bases }} bases from {{ bg_num_sequences }} background sequences. {{ '%.1f%%' % (bg_unknown * 100) }} of bases were unknown. Other bases were distributed as:

{% endif %}

Other outputs

{% if tomtom_url %} View TOMTOM output that compares the discovered motifs to known motifs.
{% endif %} {% if meme_like_output %} View MEME-like output which can be used as input to downstream tools in the MEME suite.
{% endif %} View log file.

References

STEME's home page can be found at sysbio.mrc-bsu.cam.ac.uk/johns/STEME/. If you find STEME useful, please cite: If you have any questions about STEME or problems using STEME please email.

Runtime

STEME (version {{ version }}) was called with these options. The calculation took {{ total_duration_string }} and completed on {{ completion_date_time }}.

Glossary

E-value

The E-value quantifies the statistical significance of the motif. The best motifs have a smaller E-value. The E-value is calculated from the log-likelihood ratio (LLR), width, number of sites of the motif, the frequencies of the bases in the input sequences and the size of the input. The E-value is an estimate of the expected number of motifs with a higher LLR and the same width and number of sites that MEME would find if it were given random sequences that had the same background frequencies. On large data sets the E-value has a very wide range so STEME presents the base-10 logarithm of the E-value to avoid overflows and underflows.

Log-likelihood ratio

The log-likelihood ratio is a statistic that quantifies how different the binding sites of a motif are from the background distribution. It is the logarithm of the ratio of the likelihoods of the motif's binding sites under two distributions: the motif distribution and the background distribution. {% endblock %}