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Lincoln D Stein

Publications and source records attributed to Lincoln D Stein.

8 recordsLinked to original sources

ONCOLINER: A new solution for monitoring, improving, and harmonizing somatic variant calling across genomic oncology centers.

The characterization of somatic genomic variation associated with the biology of tumors is fundamental for cancer research and personalized medicine, as it guides the reliability and impact of cancer studies and genomic-based decisions in clinical oncology. However, the quality and scope of tumor genome analysis across cancer research centers and hospitals are currently highly heterogeneous, limiting the consistency of tumor diagnoses across hospitals and the possibilities of data sharing and data integration across studies. With the aim of providing users with actionable and personalized recommendations for the overall enhancement and harmonization of somatic variant identification across research and clinical environments, we have developed ONCOLINER. Using specifically designed mosaic and tumorized genomes for the analysis of recall and precision across somatic SNVs, insertions or deletions (indels), and structural variants (SVs), we demonstrate that ONCOLINER is capable of improving and harmonizing genome analysis across three state-of-the-art variant discovery pipelines in genomic oncology.

Humans↗

WormBase as an integrated platform for the C. elegans ORFeome.

The ORFeome project has validated and corrected a large number of predicted gene models in the nematode C. elegans, and has provided an enormous resource for proteome-scale studies. To make the resource useful to the research and teaching community, it needs to be integrated with other large-scale data sets, including the C. elegans genome, cell lineage, neurological wiring diagram, transcriptome, and gene expression map. This integration is also critical because the ORFeome data sets, like other 'omics' data sets, have significant false-positive and false-negative rates, and comparison to related data is necessary to make confidence judgments in any given data point. WormBase, the central data repository for information about C. elegans and related nematodes, provides such a platform for integration. In this report, we will describe how C. elegans ORFeome data are deposited in the database, how they are used to correct gene models, how they are integrated and displayed in the context of other data sets at the WormBase Web site, and how WormBase establishes connection with the reagent-based resources at the ORFeome project Web site.

Animals↗

The SNP Consortium website: past, present and future.

The SNP Consortium website (http://snp.cshl.org) has undergone many changes since its initial conception three years ago. The database back end has been changed from the venerable ACeDB to the more scalable MySQL engine. Users can access the data via gene or single nucleotide polymorphism (SNP) keyword searches and browse or dump SNP data to textfiles. A graphical genome browsing interface shows SNPs mapped onto the genome assembly in the context of externally available gene predictions and other features. SNP allele frequency and genotype data are available via FTP-download and on individual SNP report web pages. SNP linkage maps are available for download and for browsing in a comparative map viewer. All software components of the data coordinating center (DCC) website (http://snp.cshl.org) are open source.

Chromosome Mapping↗

WormBase: a cross-species database for comparative genomics.

WormBase (http://www.wormbase.org/) is a web-accessible central data repository for information about Caenorhabditis elegans and related nematodes. The past two years have seen a significant expansion in the biological scope of WormBase, including the integration of large-scale, genome-wide data sets, the inclusion of genome sequence and gene predictions from related species and active literature curation. This expansion of data has also driven the development and refinement of user interfaces and operability, including a new Genome Browser, new searches and facilities for data access and the inclusion of extensive documentation. These advances have expanded WormBase beyond the obvious target audience of C. elegans researchers, to include researchers wishing to explore problems in functional and comparative genomics within the context of a powerful genetic system.

Animals↗

Integrating biological databases.

Recent years have seen an explosion in the amount of available biological data. More and more genomes are being sequenced and annotated, and protein and gene interaction data are accumulating. Biological databases have been invaluable for managing these data and for making them accessible. Depending on the data that they contain, the databases fulfil different functions. But, although they are architecturally similar, so far their integration has proved problematic.

Animals↗

The Bioperl toolkit: Perl modules for the life sciences.

The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.

Algorithms↗

The generic genome browser: a building block for a model organism system database.

The Generic Model Organism System Database Project (GMOD) seeks to develop reusable software components for model organism system databases. In this paper we describe the Generic Genome Browser (GBrowse), a Web-based application for displaying genomic annotations and other features. For the end user, features of the browser include the ability to scroll and zoom through arbitrary regions of a genome, to enter a region of the genome by searching for a landmark or performing a full text search of all features, and the ability to enable and disable tracks and change their relative order and appearance. The user can upload private annotations to view them in the context of the public ones, and publish those annotations to the community. For the data provider, features of the browser software include reliance on readily available open source components, simple installation, flexible configuration, and easy integration with other components of a model organism system Web site. GBrowse is freely available under an open source license. The software, its documentation, and support are available at http://www.gmod.org.

Animals↗

Gramene, a tool for grass genomics.

Gramene (http://www.gramene.org) is a comparative genome mapping database for grasses and a community resource for rice (Oryza sativa). It combines a semi-automatically generated database of cereal genomic and expressed sequence tag sequences, genetic maps, map relations, and publications, with a curated database of rice mutants (genes and alleles), molecular markers, and proteins. Gramene curators read and extract detailed information from published sources, summarize that information in a structured format, and establish links to related objects both inside and outside the database, providing seamless connections between independent sources of information. Genetic, physical, and sequence-based maps of rice serve as the fundamental organizing units and provide a common denominator for moving across species and genera within the grass family. Comparative maps of rice, maize (Zea mays), sorghum (Sorghum bicolor), barley (Hordeum vulgare), wheat (Triticum aestivum), and oat (Avena sativa) are anchored by a set of curated correspondences. In addition to sequence-based mappings found in comparative maps and rice genome displays, Gramene makes extensive use of controlled vocabularies to describe specific biological attributes in ways that permit users to query those domains and make comparisons across taxonomic groups. Proteins are annotated for functional significance using gene ontology terms that have been adopted by numerous model species databases. Genetic variants including phenotypes are annotated using plant ontology terms common to all plants and trait ontology terms that are specific to rice. In this paper, we present a brief overview of the search tools available to the plant research community in Gramene.

Avena↗