Dataset Information

DNannotator: Annotation software tool kit for regional genomic sequences.

ABSTRACT: Sequence annotation is essential for genomics-based research. Investigators of a specific genomic region who have developed abundant local discoveries such as genes and genetic markers, or have collected annotations from multiple resources, can be overwhelmed by the difficulty in creating local annotation and the complexity of integrating all the annotations. Presenting such integrated data in a form suitable for data mining and high-throughput experimental design is even more daunting. DNannotator, a web application, was designed to perform batch annotation on a sizeable genomic region. It takes annotation source data, such as SNPs, genes, primers, and so on, prepared by the end-user and/or a specified target of genomic DNA, and performs de novo annotation. DNannotator can also robustly migrate existing annotations in GenBank format from one sequence to another. Annotation results are provided in GenBank format and in tab-delimited text, which can be imported and managed in a database or spreadsheet and combined with existing annotation as desired. Graphic viewers, such as Genome Browser or Artemis, can display the annotation results. Reference data (reports on the process) facilitating the user's evaluation of annotation quality are optionally provided. DNannotator can be accessed at http://sky.bsd.uchicago.edu/DNannotator.htm.

SUBMITTER: Liu C

PROVIDER: S-EPMC168949 | biostudies-literature | 2003 Jul

REPOSITORIES: biostudies-literature

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DNannotator: Annotation software tool kit for regional genomic sequences.

Liu Chunyu C Bonner Tom I TI Nguyen Tu T Lyons Jennifer L JL Christian Susan L SL Gershon Elliot S ES

Nucleic acids research 20030701 13

Sequence annotation is essential for genomics-based research. Investigators of a specific genomic region who have developed abundant local discoveries such as genes and genetic markers, or have collected annotations from multiple resources, can be overwhelmed by the difficulty in creating local annotation and the complexity of integrating all the annotations. Presenting such integrated data in a form suitable for data mining and high-throughput experimental design is even more daunting. DNannota ...[more]

PMID: 12824405

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Project description:BACKGROUND: Repeat-rich regions such as centromeres receive less attention than their gene-rich euchromatic counterparts because the former are difficult to assemble and analyze. Our objectives were to 1) map all ten centromeres onto the maize genetic map and 2) characterize the sequence features of maize centromeres, each of which spans several megabases of highly repetitive DNA. Repetitive sequences can be mapped using special molecular markers that are based on PCR with primers designed from two unique "repeat junctions". Efficient screening of large amounts of maize genome sequence data for repeat junctions, as well as key centromere sequence features required the development of specific annotation software. RESULTS: We developed JunctionViewer to automate the process of identifying and differentiating closely related centromere repeats and repeat junctions, and to generate graphical displays of these and other features within centromeric sequences. JunctionViewer generates NCBI BLAST, WU-BLAST, cross_match and MUMmer alignments, and displays the optimal alignments and additional annotation data as concise graphical representations that can be viewed directly through the graphical interface or as PostScript output.This software enabled us to quickly characterize millions of nucleotides of newly sequenced DNA ranging in size from single reads to assembled BACs and megabase-sized pseudochromosome regions. It expedited the process of generating repeat junction markers that were subsequently used to anchor all 10 centromeres to the maize map. It also enabled us to efficiently identify key features in large genomic regions, providing insight into the arrangement and evolution of maize centromeric DNA. CONCLUSIONS: JunctionViewer will be useful to scientists who wish to automatically generate concise graphical summaries of repeat sequences. It is particularly valuable for those needing to efficiently identify unique repeat junctions. The scalability and ability to customize homology search parameters for different classes of closely related repeat sequences make this software ideal for recurring annotation (e.g., genome projects that are in progress) of genomic regions that contain well-defined repeats, such as those in centromeres. Although originally customized for maize centromere sequence, we anticipate this software to facilitate the analysis of centromere and other repeat-rich regions in other organisms.

Project description:In order that biological meaning may be derived and testable hypotheses may be built from proteomics experiments, assignments of proteins identified by mass spectrometry or other techniques must be supplemented with additional notation, such as information on known protein functions, protein-protein interactions, or biological pathway associations. Collecting, organizing, and interpreting this data often requires the input of experts in the biological field of study, in addition to the time-consuming search for and compilation of information from online protein databases. Furthermore, visualizing this bulk of information can be challenging due to the limited availability of easy-to-use and freely available tools for this process. In response to these constraints, we have undertaken the design of software to automate annotation and visualization of proteomics data in order to accelerate the pace of research. Here we present the Software Tool for Researching Annotations of Proteins (STRAP), a user-friendly, open-source C# application. STRAP automatically obtains gene ontology (GO) terms associated with proteins in a proteomics results ID list using the freely accessible UniProtKB and EBI GOA databases. Summarized in an easy-to-navigate tabular format, STRAP results include meta-information on the protein in addition to complementary GO terminology. Additionally, this information can be edited by the user so that in-house expertise on particular proteins may be integrated into the larger data set. STRAP provides a sortable tabular view for all terms, as well as graphical representations of GO-term association data in pie charts (biological process, cellular component, and molecular function) and bar charts (cross comparison of sample sets) to aid in the interpretation of large data sets and differential analyses experiments. Furthermore, proteins of interest may be exported as a unique FASTA-formatted file to allow for customizable re-searching of mass spectrometry data, and gene names corresponding to the proteins in the lists may be encoded in the Gaggle microformat for further characterization, including pathway analysis. STRAP, a tutorial, and the C# source code are freely available from http://cpctools.sourceforge.net.

Dataset Information

DNannotator: Annotation software tool kit for regional genomic sequences.

Publications

DNannotator: Annotation software tool kit for regional genomic sequences.

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