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R W Cottingham

Publications and source records attributed to R W Cottingham.

10 recordsLinked to original sources
PubMed1996

Improvements to the GDB Human Genome Data Base.

Version 6.0 of the Human Genome Data Base introduces a number of significant improvements over previous releases of GDB. The most important of these are revised data representations for genes and genomic maps and a new curatorial model for the database. GDB 6.0 is the first major genomic database to provide read/write access directly to the scientific community, including capabilities for third-party annotation. The revised database can represent all major categories of genetic and physical maps, along with the underlying order and distance information used to construct them. The improved representation permits more sophisticated map queries to be posed and supports the graphical display of maps. In addition the new GDB has a richer model for gene information, better suited for supporting cross-references to databases describing gene function, structure, products, expression and associated phenotypes.

Animals↗
PubMed1996

Error detection for genetic data, using likelihood methods.

As genetic maps become denser, the effect of laboratory typing errors becomes more serious. We review a general method for detecting errors in pedigree genotyping data that is a variant of the likelihood-ratio test statistic. It pinpoints individuals and loci with relatively unlikely genotypes. Power and significance studies using Monte Carlo methods are shown by using simulated data with pedigree structures similar to the CEPH pedigrees and a larger experimental pedigree used in the study of idiopathic dilated cardiomyopathy (DCM). The studies show the index detects errors for small values of theta with high power and an acceptable false positive rate. The method was also used to check for errors in DCM laboratory pedigree data and to estimate the error rate in CEPH-chromosome 6 data. The errors flagged by our method in the DCM pedigree were confirmed by the laboratory. The results are consistent with estimated false-positive and false-negative rates obtained using simulation.

Cardiomyopathy, Dilated↗
PubMed1994

Polymorphisms and linkage analysis for ICAM-1 and the selectin gene cluster.

Genetic polymorphisms in leukocyte and endothelial cell adhesion molecules may be important variables with regard to susceptibility to multifactorial disease processes that include an inflammatory component. For this reason, polymorphisms were sought for intercellular adhesion molecule-1 (ICAM-1; gene symbol ICAM1) and for the three genes in the selectin cluster, P-selectin, L-selectin, and E-selectin (gene symbols SELP, SELL, and SELE, respectively). Two amino acid polymorphisms were identified for ICAM-1; Gly or Arg at codon 241 and Lys or Glu at codon 469. Dinucleotide repeat polymorphisms were identified in the 3'-untranslated region for ICAM-1 and in intron 9 for P-selectin. Restriction fragment length polymorphisms were found using cDNAs for each of the three selectin genes as probes; E-selectin with BglII, P-selectin with ScaI, and L-selectin with HincII. Linkage analysis was performed for the selectin gene cluster and for ICAM-1 using the CEPH families; ICAM-1 is very tightly linked to the LDL receptor on chromosome 19, and the selectin cluster is linked to markers at chromosome 1q23.

Base Sequence↗
PubMed1993

Faster sequential genetic linkage computations.

Linkage analysis using maximum-likelihood estimation is a powerful tool for locating genes. As available data sets have grown, the computation required for analysis has grown exponentially and become a significant impediment. Others have previously shown that parallel computation is applicable to linkage analysis and can yield order-of-magnitude improvements in speed. In this paper, we demonstrate that algorithmic modifications can also yield order-of-magnitude improvements, and sometimes much more. Using the software package LINKAGE, we describe a variety of algorithmic improvements that we have implemented, demonstrating both how these techniques are applied and their power. Experiments show that these improvements speed up the programs by an order of magnitude, on problems of moderate and large size. All improvements were made only in the combinatorial part of the code, without restoring to parallel computers. These improvements synthesize biological principles with computer science techniques, to effectively restructure the time-consuming computations in genetic linkage analysis.

Algorithms↗
PubMed1992

Genetic linkage analysis of bipolar affective disorder in an Old Order Amish pedigree.

We have used genetic linkage analysis in an effort to identify a gene responsible for bipolar affective disorder (BAD) in an Old Order Amish pedigree. The initial study of this pedigree showed strong evidence for linkage of the chromosome 11p15 markers HRAS1 and the insulin gene (INS) to BAD, whereas a second report found no evidence for linkage. We have independently determined the INS and HRAS1 genotypes from 81 individuals in this pedigree. A polymerase chain reaction (PCR) assay was used to score INS alleles that are difficult to distinguish from one another by conventional agarose gel electrophoresis. In addition, we used four separate diagnostic models to score individuals with psychiatric illness as either affected or unaffected. No evidence of significant linkage between BAD and the markers was found with either two-point or multipoint analysis regardless of which diagnostic model was used. However, exclusion of the region of chromosome 11 between INS and RAS1 as a possible location for the BAD gene in this family depended on the diagnostic model. Further genetic linkage studies with additional DNA markers that span the genome are necessary to determine the chromosomal location of the BAD gene in this family.

Base Sequence↗
PubMed1992

Genetic mapping of four dinucleotide repeat loci, DXS453, DXS458, DXS454, and DXS424, on the X chromosome using multiplex polymerase chain reaction.

Dinucleotide CA repeat sequences in the human genome have been shown to be highly polymorphic due to variation in the length of the repeat-containing segment. Therefore, these markers can serve as anchor loci in the construction of a high-resolution genetic map of the human genome. In this study, we improved the efficiency of typing dinucleotide repeats using multiplex polymerase chain reaction (PCR). Dinucleotide repeat sequences of four previously identified markers (DXS453, DXS458, DXS454, and DXS424) on the long arm of the X chromosome were simultaneously amplified in a single PCR reaction. This multiplex PCR was applied to genotype individuals from the 40 CEPH reference families, and the genotypic data were used to determine the map position of the four loci with respect to eight reference markers in the Xq region by linkage analysis.

Base Sequence↗
PubMed1991

A gene for limb-girdle muscular dystrophy maps to chromosome 15 by linkage.

Limb-girdle muscular dystrophy (LGMD) is inherited as a monogenic, autosomal recessive trait. A genetically homogeneous group of families from the Isle of La Réunion, comprising individuals at high risk for this disorder, was systematically analysed using a panel of 85 polymorphic markers spanning approximately 30% of the human genome. Linkage was detected between the LGMD gene and the marker D15S25, uncovered with the probe pTHH114 and restriction enzyme RsaI (lod score = 5.52 at a 0 = 0.0), localising this gene onto chromosome 15. Such a lod score corresponds to odds of 3.3 x 105 in favor of linkage versus absence of linkage. Additional families from other populations will need to be examined before the role of this newly identified locus can be understood.

Chromosome Mapping↗
PubMedDate not supplied

Parallelization of general-linkage analysis problems.

We describe a parallel implementation of a genetic-linkage analysis program that achieves good speed improvement, even for analyses on a single pedigree and with a single starting recombination fraction vector. Our parallel implementation has been run on three different platforms: an Ethernet network of workstations, a higher-bandwidth asynchronous transfer mode (ATM) network of workstations, and a shared-memory multiprocessor. The same program, written in a shared-memory programming style, is used on all platforms. On the workstation networks, the hardware does not provide shared memory, so the program executes on a distributed shared memory system that implements shared memory in software. These three platforms represent different points on the price/performance scale. Ethernet networks are cheap and omnipresent, ATM networks are an emerging technology that offers higher bandwidth, and shared-memory multiprocessors offer the best performance because communication is implemented entirely by hardware. On 8 processors and for the longer runs, we achieve speedups between 3.5 and 5 on the Ethernet network and between 4.8 and 6 on the ATM network. On the shared-memory multiprocessor, we achieve speedups in the 5.5-6.5 range for all runs.

Algorithms↗
PubMedDate not supplied

Avoiding recomputation in linkage analysis.

We describe four improvements we have implemented in a version of the genetic linkage analysis programs in the LINKAGE package: subdivision of recombination classes, better handling of loops, better coordination between the optimization and output routines, and a checkpointing facility. The unifying theme for all the improvements is to store a small amount of data to avoid expensive recomputation of known results. The subdivision of recombination classes improves on a method of Lathrop and Lalouel [Am J Hum Genet 1988;42:498-505]. The new method of handling loops extends a proposal of Lange and Elston [Hum Hered 1975;25:95-105] for loopless pedigrees with multiple nuclear families at the earliest generation. From a practical point of view, the most important improvement may be the checkpointing facility which allows the user to carry out linkage computations that are much longer than the mean-time-to-failure of the underlying computer.

Algorithms↗