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D Fredman

Publications and source records attributed to D Fredman.

4 recordsLinked to original sources

HGVbase: a curated resource describing human DNA variation and phenotype relationships.

The Human Genome Variation Database (HGVbase; http://hgvbase.cgb.ki.se) has provided a curated summary of human DNA variation for more than 5 years, thus facilitating research into DNA sequence variation and human phenotypes. The database has undergone many changes and improvements to accommodate increasing volumes and new types of data. The focus of HGVbase has recently shifted towards information on haplotypes and phenotypes, relationships between phenotypes and DNA variation, and collaborative efforts to provide a global resource for genome-phenome data. Open sharing and precise phenotype definitions are necessary to advance the current understanding of common diseases that are typified by complex aetiologies, small genetic effect sizes and multiple confounding factors that obscure positive study results. Association data will increasingly be collected as part of this new project thrust. This report describes the evolving features of HGVbase, and covers in detail the technological choices we have made to enable efficient storage and data mining of increasingly large and complex data sets.

Computational Biology↗

HGVbase: a human sequence variation database emphasizing data quality and a broad spectrum of data sources.

HGVbase (Human Genome Variation database; http://hgvbase.cgb.ki.se, formerly known as HGBASE) is an academic effort to provide a high quality and non-redundant database of available genomic variation data of all types, mostly comprising single nucleotide polymorphisms (SNPs). Records include neutral polymorphisms as well as disease-related mutations. Online search tools facilitate data interrogation by sequence similarity and keyword queries, and searching by genome coordinates is now being implemented. Downloads are freely available in XML, Fasta, SRS, SQL and tagged-text file formats. Each entry is presented in the context of its surrounding sequence and many records are related to neighboring human genes and affected features therein. Population allele frequencies are included wherever available. Thorough semi-automated data checking ensures internal consistency and addresses common errors in the source information. To keep pace with recent growth in the field, we have developed tools for fully automated annotation. All variants have been uniquely mapped to the draft genome sequence and are referenced to positions in EMBL/GenBank files. Data utility is enhanced by provision of genotyping assays and functional predictions. Recent data structure extensions allow the capture of haplotype and genotype information, and a new initiative (along with BiSC and HUGO-MDI) aims to create a central repository for the broad collection of clinical mutations and associated disease phenotypes of interest.

Base Sequence↗

SNP association studies in Alzheimer's disease highlight problems for complex disease analysis.

Genetic linkage and association analyses are two distinct approaches to understanding the genetic etiology of complex disease. Association analysis has become particularly popular in recent times, but the true utility of the strategy remains uncertain. To try to gain better insight into the relevant issues, we have used genetic association analysis to explore the etiology of Alzheimer's disease. Our empirical findings supplement the theoretical debate, illustrating the general doubtfulness of previous positive findings and the limited ability of typical association studies based on candidate genes to discern true medium-sized signals from false positives. Improvements in genotyping technologies and increasing the number of SNPs tested, without sophisticated allowance for all other issues, could simply lead to an unmanageable overload of false-positive signals, themselves obscuring true disease associations.

Alzheimer Disease↗