Meme Software Motif
The MEME Suite allows the biologist to discover novel motifs in collections of unaligned DNA or protein sequences and to search for motif occurrences in sequence databases. The suite is comprised of a collection of tools that work together, as shown below. Not all the tools are avaliable as webservices, so to get the full power of the MEME Suite you will need to and install a local copy of the software. Motif discovery Find ungapped motifs in unaligned sequences Find short motifs in large sets of sequences Find gapped motifs in unaligned sequences, Motif search Search a sequence database for occurrences of known motifs. This program treats each motif independently and reports all putative motif occurrences below a specified p-value threshold. Search for occurences of gapped motifs, discovered by GLAM2., Search a sequence database for occurences of known motifs. This program assumes exactly one occurrence of each motif per sequence, and each sequence in the database is assigned a p-value, based on the product of the p-values of the individual motif occurrences in that sequence.
The width of each motif that MEME reports will lie within the limits you choose. [ close] This is the. Meta-MEME:Motif-basedHidden Markov Models of Protein Families W illiam N. Grundy bgrundy@cs.ucsd.edu Department of Computer Science and Engineering.
Search a sequence database for clusters of known motifs. Mcast employs a motif-based hidden Markov model, using a star topology and a novel scoring algorithm.
The motifs may appear in any order. Additional primary tools Print the Average Motif Affinity score of each sequence in a database. The score is calculated by averaging the likelihood ratio scores for all feasible binding events to the given sequence and to its reverse strand. Perform a motif enrichment analysis, outputting the names of known DNA motifs that are enriched in the input sequences. Identify centrally enriched motifs., Identify possible roles (Gene Ontology terms) for DNA binding motifs. Automate analysis of ChIP-seq data using the MEME suite., Search one or more motifs against a database of known motifs. Find enriched motif spacings., File format conversion utilities Convert an BEEML matrix file to MEME format.
Convert a CHEN matrix file to MEME format. Convert a Clustalw multiple alignment into FASTA format. Convert a Clustalw multiple alignment into Phylip format. Convert glam2 motifs to standard alignment formats.
Convert a Gene Ontology OBO file into a GO DAG file. Convert an IUPAC string to MEME format. Convert a directory of JASPAR files to MEME format. Convert MAST XML output into plain text. Convert and merge multiple MEME formatted files. Convert a PRIORITY matrix file to MEME format.
Format conversion utility for sequence data. Convert a FASTA file with short RNA sequences into motifs for DNA they might bind in MEME format.
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Convert an SCPD matrix file to MEME format. Convert a TAMO matrix file to MEME format. Convert a TRANSFAC matrix file to MEME format. Convert a UNIPROBE matrix file to MEME format. Assorted utilities Classify a string passed as a command line argument as an instance of the DNA or protein alphabet. Add q-values to ama output. Create motif logos.
Compute the distribution of priors in a. Estimate a Markov model from a FASTA file of sequences. Read and write FASTA files. Extract a random selection of the sequences in a FASTA file.
Can also subsample the sequences themselves. Fit an extreme value distribution to data. Generate sequences from a Markov model. Print statistics about sequences read from a FASTA file. Generate position-specific priors from positive (likely to contain a feature of interest) and negative (unlikely to contain a feature of interest) sequences for use as an additional input to MEME. Mask glam2 motifs out of sequences, so that weaker motifs can be found.
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Identify GO terms which are implied by other GO terms, allowing the most specific GO terms to be highlighted in the conversion to html. Print summary of MEME HTML file to standard output as plain text. Calculate the statistical power of phylogentic motif models. Remove highly similar members of a set of sequences. Compute q-values from p-values. Given a tree and an alignment, identify the intersection of the sets of sequence IDs and leaf labels. Trim the extra sequences and leaves and print the resulting alignment and tree.
Extract specified columns from a multiple alignment. Remove from an alignment all columns that correspond to a gap in a specified species. Perform phylogenetic shadowing on a given DNA alignment, using a given tree.
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File formats. (with a ). Maintenance and development of the MEME Suite is funded by the National Center for Research Resources grant NIH/NCRR R01 RR021692. The MEME Suite web server is funded by the.
Developed and maintained.