Next-generation sequencing technology provides greater sequencing capacity to identify disease-causing variations. Currently there are many alignment tools and variation detection techniques, multiple SNP data sets used to filter out benign polymorphisms with the intent of enriching for disease-causing variations, and many tools and websites for annotating variations and performing pathogenicity prediction of variations. There is no consensus or standard with regards to which tools and corresponding parameter settings for each tool is appropriate for the different application of next-generation sequencing technologies for disease-causing variation identification. We have implemented an annotation pipeline that can easily use the output from different alignment tools (BLAT, BWA, BFAST, Bowtie) typically used to align sequence from next-generation sequencing and Sanger sequencing experiments. The Automated Sequence Analysis Pipeline (ASAP) reports variations using the HGVS standardized nomenclature[1] to facilitate comparison across tools and publications. To date, we have annotated the sequence from 13 exomes in an effort to identify disease-causing mutations.

MOTIVATION: High accuracy of data always governs the large-scale gene discovery projects. The data should not only be trustworthy but should be correctly annotated for various features it contains. Sequence errors are inherent in single-pass sequences such as ESTs obtained from automated sequencing. These errors further complicate the automated identification of EST-related sequencing. A tool is required to prepare the data prior to advanced annotation processing and submission to public databases. RESULTS: This paper describes ESTprep, a program designed to preprocess expressed sequence tag (EST) sequences. It identifies the location of features present in ESTs and allows the sequence to pass only if it meets various quality criteria. Use of ESTprep has resulted in substantial improvement in accurate EST feature identification and fidelity of results submitted to GenBank. AVAILABILITY: The program is freely available for download from http://genome.uiowa.edu/pubsoft/software.html

MOTIVATION: In gene discovery projects based on EST sequencing, effective post-sequencing identification methods are important in determining tissue sources of ESTs within pooled cDNA libraries. In the past, such identification efforts have been characterized by higher than necessary failure rates due to the presence of errors within the subsequence containing the oligo tag intended to define the tissue source for each EST. RESULTS: A large-scale EST-based gene discovery program at The University of Iowa has led to the creation of a unique software method named UITagCreator usable in the creation of large sets of synthetic tissue identification tags. The identification tags provide error detection and correction capability and, in conjunction with automated annotation software, result in a substantial improvement in the accurate identification of the tissue source in the presence of sequencing and base-calling errors. These identification rates are favorable, relative to past paradigms. AVAILABILITY: The UITagCreator source code and installation instructions, along with detection software usable in concert with created tag sets, is freely available at http://genome.uiowa.edu/pubsoft/software.html CONTACT: [email protected]

The availability of a large number of highly informative genetic markers has made human linkage analysis faster and easier to perform. However, current linkage analysis software does not provide an organizational database into which a large body of linkage data can be easily stored and manipulated. This manual entry and editing of linkage data is often time consuming and prone to typing errors. In addition, the large number of alleles in many of these markers must be reduced in order to perform linkage analysis with multiple loci across large genetic distances. This reduction in allele number is often difficult and confusing, especially in large pedigrees. We have taken advantage of the Macintosh-based Hypercard program to develop an interface with which linkage data can be easily stored, retrieved and edited. For each family, the components of the pedigree, including ID numbers, sex and affection status, only need to be entered once. The program (Linkage Interface) retrieves this information each time the data from a new polymorphic marker is entered. Linkage Interface has flexible editing capabilities that allow the user to change any portion of the pedigree, including the addition or deletion of family members, without affecting previously entered genotype data. Linkage Interface can also analyze both the pedigree and marker data and will detect any inconsistencies in inheritance patterns. In addition, the program can reduce the number of alleles for a polymorphic marker. Linkage Interface will then compare the 'reduced' data to the original marker data and assists in maintaining all informative meioses by pointing out which meioses have become non-informative.(ABSTRACT TRUNCATED AT 250 WORDS)