The University of Arizona
TCW Summary
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singleTCW contains three major programs:

  1. runSingleTCW
    • Input: sequences and optional counts, where any of the following are valid:
      1. Load RNA-seq transcripts and count data with optional replicates.
      2. Load protein sequences and spectra (count) data with optional replicates.
      3. Load sequences with location information (e.g. predicted genes).
      4. Assemble up to ~1M sequences, such as: transcript sets, paired-end Sanger ESTs, or a mix of transcripts and ESTs.
    • Annotation:
      1. Annotate sequences with one or more nucleotide or protein databases (called annoDBs). A script, newUPver.pl is provided to download taxonomic UniProt databases. The following programs can be used for searching: the new super-fast diamond or ublast, or the standard blast.
      2. If UniProt is used, GO annotations along with EC, KEGG and Pfam identifiers are extracted and entered into the database. A script, newGOver.pl is provided to create the GO MySQL database for use by TCW.
      3. Compute ORFS and GC content.
    • All data and results are stored in a MySQL database.
  2. runDE:
    • An interface to several R packages (EdgeR, DESeq) for calculating differential of sequences. Additionally, it can execute a user-provided R script for DE calculation.
    • If UniProt is used and GO entered, the GOseq R program can be used to compute differential GO terms.
  3. viewSingleTCW:
    • Query and view the results. There are various filters, for example, filters are provided specific to taxonomic databases, trimmed GOs, filter by annotation, etc.
multiTCW contains two major programs:
  1. runMultiTCW:
    • Builds a database of singleTCW projects.
    • Runs blast to compare the sequences from the input TCWs.
    • Clusters them into ortholog groups. They can be clustered with OrthoMCL and/or TCW transitive closure, and user-supplied clusters can be uploaded. Multiple ortholog clustering can be in the database for query.
  2. viewMultiTCW:
    • Query and view the results. The results can be filtered on various attributes. A cluster can be viewed graphically with the results of Muscle alignment or pairwise alignment.

Email: tcw@agcol.arizona.edu
References:
C. Soderlund, W. Nelson and S. Goff (2014) Allele Workbench: transcriptome pipeline and interactive graphics for allele-specific expression. PLOS ONE. Link
Describes a pipeline that can be used with TCW, plus a new GO trim algorithm.
 
C. Soderlund, W. Nelson, M. Willer and D. Gang (2013) TCW: Transcriptome Computational Workbench. PLOS ONE. Link
Describes the TCW package.
 
C. Soderlund, E. Johnson, M. Bomhoff, and A. Descour (2009) PAVE: Program for Assembling and Viewing ESTs. BMC Genomics. Link
Describes the assembly algorithm.

Email Comments To: tcw@agcol.arizona.edu