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MEME suite

MEME suite is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand MEME suite rather than just read about it. In short: The MEME suite is a collection of tools for the discovery and analysis of sequence motifs. It was developed by Timothy Bailey in the Department of Pharmacology at the University of Nevada, Reno, and William Stafford Noble in the Department of Genome Sciences at the University of Washington.

Key takeaways

  • MEME suite belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect MEME suite to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of MEME suite from memory before moving on to harder problems.

Reference excerpt

The MEME suite is a collection of tools for the discovery and analysis of sequence motifs. It was developed by Timothy Bailey in the Department of Pharmacology at the University of Nevada, Reno, and William Stafford Noble in the Department of Genome Sciences at the University of Washington. It can be installed as standalone binaries for offline use or used through a web-interface.

Motif discovery

MEME

Multiple Expectation maximizations for Motif Elicitation (MEME) is a tool for discovering motifs in a group of related DNA or protein sequences. MEME takes as input a group of DNA or protein sequences and outputs as many motifs as requested up to a user-specified statistical confidence threshold. MEME uses statistical modeling techniques to automatically choose the best width, number of occurrences, and description for each motif.

GLAM2 Gapped local alignment of motifs (GLAM 2) is a tool for discovering gapped motifs in a group of DNA or protein sequences. Unlike MEME, GLAM2 does not try to find several different motifs all in one go. Instead, it performs replicates: it tries to find the best possible motif multiple times.

DREME Discriminative Regular Expression Motif Elicitation (DREME) is a tool for discovering motifs in large collections of sequences. DREME is computationally efficient and therefore is suitable for motif search on large data sets derived from ChIP-seq (Chromatin immunoprecipitation followed by sequencing) experiments. In the interest of computational efficiency, DREME finds only motifs that can be expressed in the IUPAC alphabet, which contains the standard DNA alphabet ACGT as well as eleven 'wildcard' characters (for example, R indicates either A or G).

MEME-ChIP MEME-ChIP is a tool for discovering motifs in data sets derived from ChIP-seq (Chromatin immunoprecipitation followed by sequencing) experiments.

Motif search

FIMO Find Individual Motif Occurrences (FIMO) is a tool for finding instances of motifs in a sequence database. FIMO searches the database for the provided motifs, and reports a q-value for each match.

GLAM2SCAN GLAM2SCAN is a tool for finding occurrences of a GLAM2 motif in a sequence database.

MAST Motif Alignment & Search Tool (MAST) is a tool for searching biological sequence databases for sequences that contain an occurrence of each motif in a given set of motifs. MAST scores the matches and reports p-values for four types of events:

Position p-value: The p-value of a match of a given position within a sequence to a motif is defined as the probability of a randomly selected position in a randomly generated sequence having a match score at least as large as that of the given position. Note:If MAST is combining reverse complement DNA strands, the position p-value is not corrected for multiple tests. Sequence p-value: The p-value of a match of a sequence to a motif is defined as the probability of a randomly generated sequence of the same length having a match score at least as large as the largest match score of any position in the sequence. Combined p-value: The p-value of a match of a sequence to a group of motifs is defined as the probability of a randomly generated sequence of the same length having sequence p-values whose product is at least as small as the product of the sequence p-values of the matches of the motifs to the given sequence. E-value: The E-value of the match of a sequence in a database to a group of motifs is defined as the expected number of sequences in a random database of the same size that would match the motifs as well as the sequence does and is equal to the combined p-value of the sequence times the number of sequences in the database.

Motif enrichment analysis

SpaMo Spaced Motif Analysis Tool (SpaMo) is a tool for inferring interactions between transcription factors. SpaMo takes a set of sequences (typically sequences surrounding ChIP-seq peaks), a motif represented in these sequences, and a database of known motifs. SpaMo searches the database for instances of database motifs enriched in sites neighboring the given motif. These enrichments suggest physical interaction between the factors that bind each motif.

CentriMo Central Motif Enrichment Analysis (CentriMo) is a tool for inferring direct DNA binding from ChIP-seq data. CentriMo is based on the observation that the positional distribution of binding sites matching the direct-binding motif tends to be unimodal, well centered and maximal in the precise center of the ChIP-seq peak regions. CentriMo takes a set of sequences and plots the occurrence of motifs relative to the ChIP-seq peak. Motifs that occur exclusively at the peak provide good evidence of direct binding, while motifs that do not occur in a consistent position relative to the peak may not bind directly.

Motif cluster search

MCAST Motif Cluster Alignment and Search Tool (MCAST) is a tool for searching a sequence database for statistically significant clusters of non-overlapping occurrences of a set of motifs. Such clusters may represent regulatory modules.

Motif comparison

TOMTOM Tomtom is a tool for comparing a DNA motif to a database of known motifs. TOMTOM searches for statistically significantly similar motifs to the query motif. TOMTOM is useful for determining whether a discovered motif is novel or is a variation of a known motif.

Motif function analysis

GOMO Gene Ontology for MOtifs (GOMO) is a tool for identifying possible roles for DNA binding motifs. It does so by comparing genes the motif occurs upstream of to a Gene Ontology database. If the motif occurs statistically significantly upstream of genes related to a particular function (for example, lactose digestion), it suggests that the transcription factor that binds the motif may regulate that function (for example, by promoting transcription of proteins that digest lactose).

References

External links Official website.

Worked examples

Example 1 — a first encounter with MEME suite

Start with the simplest possible case. Write down what MEME suite claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to MEME suite before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about MEME suite ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of MEME suite

In research
MEME suite appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses MEME suite in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
MEME suite is common in secondary-school and first-year university syllabi. It links to neighbouring topics Bioinformatics software, Science software for Linux, so understanding it makes those chapters shorter.
In everyday life
Look for MEME suite outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study MEME suite in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what MEME suite means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain MEME suite out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is MEME suite in simple terms?

The MEME suite is a collection of tools for the discovery and analysis of sequence motifs. It was developed by Timothy Bailey in the Department of Pharmacology at the University of Nevada, Reno, and William Stafford Noble in the Department of Genome Sciences at the University of Washington.

Why does MEME suite matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study MEME suite?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on MEME suite.

Tags

  • Bioinformatics software
  • Science software for Linux

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