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T P Speed

Publications and source records attributed to T P Speed.

At least 19 recordsLinked to original sources
PubMed2006

A genetic screen for behavioral mutations that perturb dopaminergic homeostasis in mice.

Disruption of dopaminergic (DA) systems is thought to play a central role in the addictive process and in the pathophysiology of schizophrenia. Although inheritance plays an important role in the predisposition to these disorders, the genetic basis of this is not well understood. To provide additional insight, we have performed a modifier screen in mice designed to identify mutations that perturb DA homeostasis. With a genetic background sensitized by a mutation in the dopamine transporter (DAT), we used random chemical mutagenesis and screened for mutant mice with locomotor abnormalities. Four mutant lines were identified with quantitatively elevated levels of locomotor activity. Mapping of mutations in these lines identified two loci that alter activity only when dopamine levels are elevated by a DAT mutation and thus would only have been uncovered by this type of approach. One of these quantitative trait loci behaves as an enhancer of DA neurotransmission, whereas the other may act as a suppressor. In addition, we also identified three loci which are not dependent on the sensitized background but which also contribute to the overall locomotor phenotype.

Animals↗
PubMed2005

A comparison of match-only algorithms for the analysis of Plasmodium falciparum oligonucleotide arrays.

This study is motivated by two data sets which employ a custom Plasmodium falciparum version of the Affymetrix GeneChip, containing only perfect match (PM) oligonucleotides. A PM-only chip cannot be analysed using the standard Affymetrix-supplied software. We compared the performance of three match-only algorithms on these data: the Match Only Integral Distribution (MOID) algorithm, Robust Multichip Analysis (RMA), and the Model Based Expression Index (MBEI). We validated the differential expression of several genes using quantitative reverse transcriptase-PCR. We also performed a comparison using two publicly available 'benchmarking' data sets: the Latin Square spike-in data set generated by Affymetrix, and the Gene Logic dilution series. Since we know what the true fold changes are in these special data sets, they are helpful for assessment of expression algorithms.

Algorithms↗
PubMed2003

A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.

MOTIVATION: When running experiments that involve multiple high density oligonucleotide arrays, it is important to remove sources of variation between arrays of non-biological origin. Normalization is a process for reducing this variation. It is common to see non-linear relations between arrays and the standard normalization provided by Affymetrix does not perform well in these situations. RESULTS: We present three methods of performing normalization at the probe intensity level. These methods are called complete data methods because they make use of data from all arrays in an experiment to form the normalizing relation. These algorithms are compared to two methods that make use of a baseline array: a one number scaling based algorithm and a method that uses a non-linear normalizing relation by comparing the variability and bias of an expression measure. Two publicly available datasets are used to carry out the comparisons. The simplest and quickest complete data method is found to perform favorably. AVAILABILITY: Software implementing all three of the complete data normalization methods is available as part of the R package Affy, which is a part of the Bioconductor project http://www.bioconductor.org. SUPPLEMENTARY INFORMATION: Additional figures may be found at http://www.stat.berkeley.edu/~bolstad/normalize/index.html

Algorithms↗
PubMed2003

Deriving statistical models for predicting peptide tandem MS product ion intensities.

Improved search algorithms and scoring functions are required before the identification of peptide tandem MS data can be considered to be fully reliable and automatable. The development of models that can accurately predict product ion spectra from a peptide sequence would certainly help achieve this goal, but this firstly requires a better understanding of the process of fragmentation of peptides in the gas-phase. We summarize recent developments in this area and show that the prediction of product ion spectra is feasible and should improve the identification of peptide tandem MS data, especially for peptides that currently give low or insignificant scores with current search algorithms.

Algorithms↗
PubMed2001

Power and robustness of a score test for linkage analysis of quantitative traits using identity by descent data on sib pairs.

Identification of genes involved in complex traits by traditional (lod score) linkage analysis is difficult due to many complicating factors. An unfortunate drawback of non-parametric procedures in general, though, is their low power to detect genetic effects. Recently, Dudoit and Speed [2000] proposed using a (likelihood-based) score test for detecting linkage with IBD data on sib pairs. This method uses the likelihood for theta, the recombination fraction between a trait locus and a marker locus, conditional on the phenotypes of the two sibs to test the null hypothesis of no linkage (theta = (1/2)). Although a genetic model must be specified, the approach offers several advantages. This paper presents results of simulation studies characterizing the power and robustness properties of this score test for linkage, and compares the power of the test to the Haseman-Elston and modified Haseman-Elston tests. The score test is seen to have impressively high power across a broad range of true and assumed models, particularly under multiple ascertainment. Assuming an additive model with a moderate allele frequency, in the range of p = 0.2 to 0.5, along with heritability H = 0.3 and a moderate residual correlation rho = 0.2 resulted in a very good overall performance across a wide range of trait-generating models. Generally, our results indicate that this score test for linkage offers a high degree of protection against wrong assumptions due to its strong robustness when used with the recommended additive model.

Computer Simulation↗
PubMed2001

Phat--a gene finding program for Plasmodium falciparum.

We describe and assess the performance of the gene finding program pretty handy annotation tool (Phat) on sequence from the malaria parasite Plasmodium falciparum. Phat is based on a generalized hidden Markov model (GHMM) similar to the models used in GENSCAN, Genie and HMMgene. In a test set of 44 confirmed gene structures Phat achieves nucleotide-level sensitivity and specificity of greater than 95%, performing as well as the other P. falciparum gene finding programs Hexamer and GlimmerM. Phat is particularly useful for P. falciparum and other eukaryotes for which there are few gene finding programs available as it is distributed with code for retraining it on new organisms. Moreover, the full source code is freely available under the GNU General Public License, allowing for users to further develop and customize it.

Algorithms↗
PubMed2001

Analysis of cDNA microarray images.

Microarrays are part of a new class of biotechnologies that allow the monitoring of expression levels for thousands of genes simultaneously. Image analysis is an important aspect of microarray experiments, one that can have a potentially large impact on subsequent analyses, such as clustering or the identification of differentially expressed genes. This paper reviews a number of existing image analysis methods used on cDNA microarray data. In particular, it describes and discusses the different segmentation and background adjustment methods. It was found that in some cases background adjustment can substantially reduce the precision--that is, increase the variability of low-intensity spot values. In contrast, the choice of segmentation procedure seems to have a smaller impact.

Data Interpretation, Statistical↗
PubMed2000

Power of a score test for quantitative trait linkage analysis of relative pairs.

The score test of Dudoit and Speed [(2000) Biostatistics 1:1-26] to detect linkage between a trait locus and a marker locus, using identity by descent data on sib pairs, is extended to other types of relative pairs (grandparent/grandchild, avuncular, and half-sib relationships). The test is based on the likelihood of the recombination fraction theta between trait and marker loci, conditional on phenotypes of the relatives. We present results of simulation studies characterizing power and robustness properties of this linkage score test, and compare the power of the score test to that of the classical and modified Haseman-Elston tests. The score test has considerable power, particularly under sampling schemes where selection is on double probands. Use of a generic additive model [Goldstein et al., submitted] with allele frequency p = 0.2, heritability H = 0.3, and a moderate residual correlation of rho = 0.2 resulted in a very good overall performance across a wide range of trait-generating models.

Computer Simulation↗
PubMed2000

DNA sequencing with transposons.

The use of transposons offers the possibility of a directed approach to DNA sequencing, where a target DNA up to about 6kb in length can be sequenced quickly and with minimal redundancy. Transposons are mobile DNA elements which can be inserted in a reasonably random fashion into the target DNA. An important part of this process is the location of the transposon insertions (known as mapping) and the selection of a sensible subset of transposons to use as priming sites for sequencing reactions. This paper presents a probabilistic method of scoring selected subsets of transposons and a graph-theoretic algorithm for selection of a subset of maximal score.

Algorithms↗
PubMed2000

A score test for the linkage analysis of qualitative and quantitative traits based on identity by descent data from sib-pairs.

We propose a general likelihood-based approach to the linkage analysis of qualitative and quantitative traits using identity by descent (IBD) data from sib-pairs. We consider the likelihood of IBD data conditional on phenotypes and test the null hypothesis of no linkage between a marker locus and a gene influencing the trait using a score test in the recombination fraction theta between the two loci. This method unifies the linkage analysis of qualitative and quantitative traits into a single inferential framework, yielding a simple and intuitive test statistic. Conditioning on phenotypes avoids unrealistic random sampling assumptions and allows sib-pairs from differing ascertainment mechanisms to be incorporated into a single likelihood analysis. In particular, it allows the selection of sib-pairs based on their trait values and the analysis of only those pairs having the most informative phenotypes. The score test is based on the full likelihood, i.e. the likelihood based on all phenotype data rather than just differences of sib-pair phenotypes. Considering only phenotype differences, as in Haseman and Elston (1972) and Kruglyak and Lander (1995), may result in important losses in power. The linkage score test is derived under general genetic models for the trait, which may include multiple unlinked genes. Population genetic assumptions, such as random mating or linkage equilibrium at the trait loci, are not required. This score test is thus particularly promising for the analysis of complex human traits. The score statistic readily extends to accommodate incomplete IBD data at the test locus, by using the hidden Markov model implemented in the programs MAPMAKER/SIBS and GENEHUNTER (Kruglyak and Lander, 1995; Kruglyak et al., 1996). Preliminary simulation studies indicate that the linkage score test generally matches or outperforms the Haseman-Elston test, the largest gains in power being for selected samples of sib-pairs with extreme phenotypes.

Journal Article↗
PubMed2000

Microarray expression profiling identifies genes with altered expression in HDL-deficient mice.

Based on the assumption that severe alterations in the expression of genes known to be involved in high-density lipoprotein (HDL) metabolism may affect the expression of other genes, we screened an array of >5000 mouse expressed sequence tags for altered gene expression in the livers of two lines of mice with dramatic decreases in HDL plasma concentrations. Labeled cDNA from livers of apolipoprotein AI (apoAI)-knockout mice, scavenger receptor BI (SR-BI) transgenic mice, and control mice were cohybridized to microarrays. Two-sample t statistics were used to identify genes with altered expression levels in the knockout or transgenic mice compared with control mice. In the SR-BI group we found nine array elements representing at least five genes that were significantly altered on the basis of an adjusted P value < 0.05. In the apoAI-knockout group, eight array elements representing four genes were altered compared with the control group (adjusted P < 0.05). Several of the genes identified in the SR-BI transgenic suggest altered sterol metabolism and oxidative processes. These studies illustrate the use of multiple-testing methods for the identification of genes with altered expression in replicated microarray experiments.

Animals↗
PubMed2000

The current state of multiple sclerosis genetic research.

INTRODUCTION: Multiple sclerosis (MS) is the most common genetic disease of the nervous system with onset usually in young adulthood. Four genome-wide searches in different Caucasian populations for MS susceptibility loci have been performed, but none reported any linkage at a level that would be regarded as significant according to current criteria. Significant linkage of MS to allelic variants of the major histocompatibility (MHC) locus on chromosome 6p21 has been established although its overall contribution to MS susceptibility has proven difficult to quantify. The objective of this review is not only to provide the reader with an update of MS genetics research, but also to provide a basic knowledge of the techniques being employed to map MS susceptibility genes. The different methodologies are discussed, and specific studies are reviewed in context. METHODS: This review is based on findings from original articles, however, the results of recent candidate gene studies are intended to update previous review articles. RESULTS: There remains no concrete non-MHC locus for MS, although there are enough findings of sufficient interest to warrant further investigation and optimism. Stratification of genome scan data based on MHC class II suggests that it interacts differentially with non-MHC loci and that it contributes moderately to disease susceptibility. Candidate gene studies have continued to return negative and ambiguous results, and follow-up fine mapping of suggestive linkages from the UK genome scan has proven unsuccessful in identifying significant linkages. Genetic analysis of crosses between mouse strains that are differentially susceptible to experimental allergic encephalomyelitis (EAE) has yielded linkages corresponding to putative MS susceptibility loci. However, recent successes in transgenic mice may provide an alternative to EAE, regarded by some as a poor model of MS. CONCLUSION: The first whole genome search for a common human disease was performed over five years ago, and it is now clear, from the lack success in this field, that the genetic complexity of these traits has been underestimated. The genome-wide searches for MS susceptibility genes have suffered from insufficient statistical power, which has probably been compounded by disease and genetic heterogeneity. Studies in isolated populations and better laboratory and clinical definitions of disease are both steps in the right direction to solving these problems. Not withstanding the negative effects of genetic heterogeneity, pooling of resources for meta-analyses may provide the increase in statistical power required for detection of loci that exert a moderate or small effect on disease predisposition.

Animals↗
PubMed1999

Chromosomes X, 9, and the H2 locus interact epistatically to control Leishmania major infection.

As in other infectious diseases, the outcome of a Leishmania major infection is closely tied to the T helper cell response type; progressive disease is associated with a predominant Th2 lymphocyte response, healing with a Th1 response. In mice, susceptibility is genetically con trolled, with BALB/c (C) mice being susceptible and C57BL/6 (B) mice being resistant. Using a genome-wide scan on two large populations of F2 mice created from these strains, we have shown previously that susceptibility to infection with L. major is controlled by two autosomal loci: lmr1 at the H2 locus, and lmr2 on chromosome 9. Employing a strategy to identify loci that interact, we show here that lmr1 and lmr2 interact synergistically, and we describe a new locus lmr3, lying on the X chromosome, whose effect depends on a specific lmr1 haplotype.

Animals↗
PubMed1999

An estimate of the crosstalk matrix in four-dye fluorescence-based DNA sequencing.

Color separation is an essential step of the data processing in the four-dye fluorescence detection strategy used in automated DNA sequencing. In this paper, we propose a model to describe the crosstalk phenomenon, and show how the assumptions of the model are supported by experimental data. The crosstalk matrix is estimated via a reparameterization based on a mapping between the distribution of fluorescence intensities and that of dye concentrations. An iterative algorithm is designed to implement the estimation. To evaluate the color-correction quality of a crosstalk matrix, we propose a quantitative measure based on the distribution of the color-corrected data. We illustrate this method by applying it to a sequencing trace of slab gel electrophoresis obtained at the Human Genome Center at Lawrence Berkeley National Laboratory, and that of capillary electrophoresis provided by the Department of Chemistry at UC, Berkeley. The accuracy of this method is also assessed by the bootstrap method.

Algorithms↗
PubMed1999

Relative efficiencies of the chi-square recombination models for gene mapping with human pedigree data.

In the paper by Goldstein et al. (Genomics, 1995), the authors carried out a simulation study to investigate the relative efficiencies of a no interference linkage analysis to an analysis with certain models that allow for interference. They showed that, for completely informative and independent recombination data, the analysis with the no interference model was inefficient, in the present of interference. In practice, the assumption of completely informative markers is unrealistic with data from human pedigrees. We report the results of a study investigating whether this conclusion still holds for gametes arising within pedigrees. We consider the same two mapping problems as Goldstein et al.: exclusion mapping and gene ordering. The results obtained were consistent with their findings, although the efficiency gains for analyses using the chi-square model were not as great in some cases. This is not unexpected with less than fully informative data. These results point to the need for research of developing new statistical and computational methods to incorporate interference into multipoint linkage mapping using pedigree data. This would make efficient use of available, but sometimes scarce data, especially in disease gene mapping.

Alleles↗
PubMed1998

A three-wavelength labeling approach for DNA sequencing using energy transfer primers and capillary electrophoresis.

Capillary electrophoresis DNA sequencing has been accomplished by using four different energy transfer primers and three fluorescence detection channels. Methods have also been developed to deconvolve the three-color data into the four base concentrations. The nonnegative least squares and model selection method resulted in the best accuracy. The three-color data were compared to sequencing data obtained using four detection channels and four energy transfer primers. The average accuracy rates obtained over three 500 base M13mp18 runs using three-color coding were 96% including 18 uncallable compressions and 99.6% if these compressions are excluded. The average accuracy rate obtained using four-color coding was 96.3% including 18 uncallable compressions and 99.9% if these compressions are excluded. Although it is unlikely that three-color schemes will replace four-color sequencing, these methods have exposed basic concepts that will be useful in the development of higher-order multiplex coding methods for DNA analysis.

DNA Primers↗