PEDB: the Prostate Expression Database.

The Prostate Expression Database (PEDB) is a curated relational database and suite of analysis tools designed for the study of prostate gene expression in normal and disease states. Expressed Sequence Tags (ESTs) and full-length cDNA sequences derived from more than 40 human prostate cDNA libraries are maintained and represent a wide spectrum of normal and pathological conditions. Detailed library information including tissue source, library construction methods, sequence diversity and abundance are available in a library archive. Prostate ESTs are assembled into distinct species groups using the multiple alignment program CAP2 and are annotated with information from the GenBank, dbEST and Unigene public sequence databases. Annotated sequences in PEDB are searched using the BLAST algorithm. The differential expression of each EST species can be viewed across all libraries using a Virtual Expression Analysis Tool (VEAT), a graphical user interface written in Java for intra- and inter-library species comparisons. PEDB may be accessed via the World Wide Web at http://www.mbt.washington.edu/PEDB/

Consed: a graphical tool for sequence finishing.

Sequencing of large clones or small genomes is generally done by the shotgun approach (Anderson et al. 1982). This has two phases: (1) a shotgun phase in which a number of reads are generated from random subclones and assembled into contigs, followed by (2) a directed, or finishing phase in which the assembly is inspected for correctness and for various kinds of data anomalies (such as contaminant reads, unremoved vector sequence, and chimeric or deleted reads), additional data are collected to close gaps and resolve low quality regions, and editing is performed to correct assembly or base-calling errors. Finishing is currently a bottleneck in large-scale sequencing efforts, and throughput gains will depend both on reducing the need for human intervention and making it as efficient as possible. We have developed a finishing tool, consed, which attempts to implement these principles. A distinguishing feature relative to other programs is the use of error probabilities from our programs phred and phrap as an objective criterion to guide the entire finishing process. More information is available at http:// www.genome.washington.edu/consed/consed. html.

Hopper: software for automating data tracking and flow in DNA sequencing.

MOTIVATION: Genome-scale DNA sequencing is a multistep process in which large numbers of small template clones are propagated, purified, sequenced and analyzed on acrylamide gels. A significant challenge to these projects is the scale at which the data handling must be done. Hence, large-scale sequencing facilities will benefit from tracking template DNA information (purification methods, reaction and electrophoresis conditions) in a systematic fashion. A lack of software tools that support automated sample entry, and automatic data storage, retrieval and analysis are a major hindrance to recording and using laboratory workflow information to monitor the overall quality of data production. RESULTS: The UNIX file system has been used to prototype automation of the flow of data from the ABI sequencer to a data repository. Data are automatically processed by a central Perl program, Hopper, which runs a series of programs that analyze data quality (read length estimate, fraction of indeterminate bases, and number of contaminating and repetitive sequences), assemble shotgun sequence data, and generates simple reports describing the results.