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Online Motif Discovery with WebMOTIFS

Short descriptions of the programs and modules included with TAMO are provided below. Click HERE to go back to the TAMO Homepage.

Routines for Import Executable File Description
 
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GetDataFiles.pyDownload support data files and routines over the internet.
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  HT.pyLoad/Encapsulate/Slice High-throughput (genome-scale) datasets
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 MotifMetrics.pyCompute motif overrepresentation statistics among a sequence set, as compared to all sequences in a genome. Search of highest scoring k-mer motifs.
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  MotifTools.pyKitchen-sink motif object
 
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Sitemap.pyPrint ascii-maps of motif occurence among sets of sequences
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  DataSources/GO.pyInterface to Gene Ontologies, including statistical tests.
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  DataSources/Holstege.pyInterface to expression rate data from Holstege et. al.
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  DataSources/Novartis.pyInterface to GeneAtlas.
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  DataSources/PDB.pyA very simple PDB parser for 3-D protien/DNA structures
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  DataSources/SGD.pyInterface to the SGD yeast database, including genomic sequence.
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  DataSources/Yeast6kArray.pyInterface to the 6k intergenic array, including mappings from probes to genomic features.
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  Clustering/Kmedoids.pyK-medoids algorithms for motif clustering.
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  Clustering/MotifCompare.pyUtility routines for aligning and comparing motifs
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Clustering/UPGMA.pyUPGMA algorithm for motif clustering.
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 MD/EM.pyInterface to C++ routines for MD via Expectation Maximization
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 MD/MDsupport.pyWrapper for motif-related C++ routines
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MD/MDscan.pyInterface to MDscan program.
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MD/AlignAce.pyInterface to the AlignACE program.
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MD/Meme.pyInterface to the MEME program.
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MD/TAMO_EM.pyTAMO's very own EM implementation, that allows careful control over the seeds used for search.
 
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MDconvert/ace2tamo.pyMotif File Format Conversion Programs.
The TAMO format is described here.
 
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MDconvert/kellis2tamo.py
 
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MDconvert/meme2tamo.py
 
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MDconvert/memeset2tamo.py
 
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MDconvert/tamo2table.py
 
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MDconvert/tamo2tamo.py
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 localpaths.pyPath information for TAMO
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 paths.pyMore Path information for TAMO
 
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seq/Background.pyCompute high-order Markov background model from a collection of sequences.
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 seq/FakeFasta.pyGenerate, seed, and randomly select sequences (for statistical testing.)
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 seq/Fasta.pyFast Fasta IO
 
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seq/GenerateFastas.pyGenerate a collection of sequence files from genome-wide data and sequence.
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 seq/Human.pyFast, random-access interface to human sequence.
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 util/Arith.pySeveral very useful arithmetic routines and statistical test (hypergeometric & bionomial)
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 util/PermuteTools.pyRoutines for generating sequence permutations of k-mers. Useful for coarse-grained motif search (if fused with MotifMetrics.py)
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 util/Poisson.pyPoisson statistical tests and fitting routines to Poisson distributions
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 util/WMWtest.pyWilcoxon / Mann-Whitney rank sum test
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 util/swilk.pyShapiro-Wilk normality test (interfaces to underlying C++ routine)
  Contact Ben Gordon with questions, comments or errors