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S W Guo

Publications and source records attributed to S W Guo.

At least 19 recordsLinked to original sources
PubMed2001

Quantitative quality control in microarray image processing and data acquisition.

A new integrated image analysis package with quantitative quality control schemes is described for cDNA microarray technology. The package employs an iterative algorithm that utilizes both intensity characteristics and spatial information of the spots on a microarray image for signal-background segmentation and defines five quality scores for each spot to record irregularities in spot intensity, size and background noise levels. A composite score q(com) is defined based on these individual scores to give an overall assessment of spot quality. Using q(com) we demonstrate that the inherent variability in intensity ratio measurements is closely correlated with spot quality, namely spots with higher quality give less variable measurements and vice versa. In addition, gauging data by q(com) can improve data reliability dramatically and efficiently. We further show that the variability in ratio measurements drops exponentially with increasing q(com) and, for the majority of spots at the high quality end, this improvement is mainly due to an improvement in correlation between the two dyes. Based on these studies, we discuss the potential of quantitative quality control for microarray data and the possibility of filtering and normalizing microarray data using a quality metrics-dependent scheme.

Algorithms↗
PubMed2001

Does higher concordance in monozygotic twins than in dizygotic twins suggest a genetic component?

It is widely regarded that twins can be used as a natural experiment to subject hypotheses to empirical testing regarding the contributions of genetic factors to phenotypic variability in human traits, especially behavioral traits. In genetic epidemiology, a higher concordance rate in monozygotic (MZ) twins than in dizygotic (DZ) twins is often taken as prima facie evidence for a genetic component. While twins studies have been used to estimate the contributions of genetic factors to phenotypic variability in human traits, the corresponding methodology that allows the estimation entails several crucial assumptions. The most critical is that MZ and DZ twins are equally similar environmentally. Although MZ twins are genetically more similar than DZ twins, they are often environmentally more similar. This paper demonstrates that, even in the complete absence of any genetic factor and of any biases, the greater environmental similarity alone in MZ twins can result in higher concordance rate in MZ twins than in DZ twins. This is especially true when there are multiple environmental factors, which may have multiple exposure levels and/or interact strongly, although each of them may be of low risk. This may serve as a sobering antidote to the uncritical reliance on twin studies without examining the validity of the underlying assumptions.

Environment↗
PubMed2000

Familial aggregation of environmental risk factors and familial aggregation of disease.

Almost all human diseases have been shown to aggregate familially to some degree. This familiality is generally taken as evidence for the existence of a genetic etiologic mechanism or environmental factors common to family members, or a combination of both. It has been argued that for a disease with strong familial aggregation, environmental risk factors alone are unlikely to account for such strong aggregation, unless the presumed environmental risk factors are associated with enormous risk. This paper revisits this issue through the use of a novel statistical model. Ascertainment bias aside, the author demonstrates that familial aggregation could be explained by multiple interactive risk factors, each of which may confer a low disease risk and thus contribute only a minuscule portion to disease familiality. For example, two correlated risk factors (r=0.5), each with a relative risk of 5 and acting multiplicatively, could give rise to a sibling relative risk of 1.96. Therefore, it may not be sufficient to argue for a genetic component for a disease based solely on the notion that no high risk environmental factors have been found. In view of this, there is a need to examine carefully the roles of multiple environmental risk factors in disease familiality.

Bias↗
PubMed1999

Discovery of cancer susceptibility genes: study designs, analytic approaches, and trends in technology.

Determining the genetic causes of cancers has immense public health benefits, ranging from prevention to earlier detection and treatment of disease. Although a number of cancer susceptibility genes have been successfully identified, design and analytic issues remain that challenge the current paradigm of gene discovery. Some examples are the definition and measurement of cancer phenotype, the use of intermediate end points, the choice of sample (e.g., affected relative pairs versus large extended pedigrees), the choice of analytic method [e.g., parametric logarithm of the odds (LOD) score method versus model-free methods], and the influence of gene-environment interaction on linkage analysis. Furthermore, association methods, based on either the traditional case-control study design or family-based controls, are popular choices to evaluate candidate genes or screen for linkage disequilibrium. Finally, the study design and analytic methods for gene discovery are determined to some extent by what genomic technology is feasible within the laboratory. Many of the main issues related to gene discovery, as well as trends in genomic technology that will impact on gene discovery, are discussed from the perspective of their strengths and weaknesses, pointing to areas in need of further work.

Genes↗
PubMed1998

Threshold distributions of phenylthiocarbamide (PTC) in the Chinese population.

The ability to taste phenylthiocarbamide (PTC) is a well-documented Mendelian trait. Mapping and cloning the gene(s) responsible for the PTC tasting ability would help to delineate the molecular basis for the variations in PTC tasting ability in humans and to shed new light on taste chemosensory functions. In view of the spectacular successes in genome science, the positional cloning strategy seems to be a feasible approach to the isolation of the gene(s) underlying the PTC tasting ability. As a first step toward mapping the gene(s), we collected PTC taste threshold data on 106 individuals, most of them being university students, in Shanghai, China. Using various parametric and nonparametric statistical methods, we have found that the data set is best described by a bimodal distribution. The frequency of PTC nontasters is estimated to be 10%. This is consistent with the view that the PTC nontasting ability follows a recessive mode of inheritance. Several authors had previously reported PTC data on Chinese living outside China. Our data are, to our knowledge, the first ever collected from the Chinese population within China.

Adolescent↗
PubMed1998

Linkage analysis of human leukocyte antigen (HLA) markers in familial psoriasis: strong disequilibrium effects provide evidence for a major determinant in the HLA-B/-C region.

Although psoriasis is strongly associated with certain human leukocyte antigens (HLAs), evidence for linkage to HLA markers has been limited. The objectives of this study were (1) to provide more definitive evidence for linkage of psoriasis to HLA markers in multiplex families; (2) to compare the major HLA risk alleles in these families with those determined by previous case-control studies; and (3) to localize the gene more precisely. By applying the transmission/disequilibrium test (TDT) and parametric linkage analysis, we found evidence for linkage of psoriasis to HLA-C, -B, -DR, and -DQ, with HLA-B and -C yielding the most-significant results. Linkage was detectable by parametric methods only when marker-trait disequilibrium was considered. Case-control association tests and the TDT identified alleles belonging to the EH57.1 ancestral haplotype as the major risk alleles in our sample. Among individuals carrying recombinant ancestral haplotypes involving EH57. 1, the class I markers were retained selectively among affecteds four times more often than among unaffecteds; among the few affected individuals carrying only the class II alleles from the ancestral haplotype, all but one also carried Cw6. These data show that familial and "sporadic" psoriasis share the same risk alleles. They also illustrate that substantial parametric linkage information can be extracted by accounting for linkage disequilibrium. Finally, they strongly suggest that a major susceptibility gene resides near HLA-C.

Adult↗
PubMed1998

Inflation of sibling recurrence-risk ratio, due to ascertainment bias and/or overreporting.

One widely used measure of familial aggregation is the sibling recurrence-risk ratio, which is defined as the ratio of risk of disease manifestation, given that one's sibling is affected, as compared with the disease prevalence in the general population. Known as lambdaS, it has been used extensively in the mapping of complex diseases. In this paper, I show that, for a fictitious disease that is strictly nongenetic and nonenvironmental, lambdaS can be dramatically inflated because of misunderstanding of the original definition of lambdaS, ascertainment bias, and overreporting. Therefore, for a disease of entirely environmental origin, the lambdaS inflation due to ascertainment bias and/or overreporting is expected to be more prominent if the risk factor also is familially aggregated. This suggests that, like segregation analysis, the estimation of lambdaS also is prone to ascertainment bias and should be performed with great care. This is particularly important if one uses lambdaS for exclusion mapping, for discrimination between different genetic models, and for association studies, since these practices hinge tightly on an accurate estimation of lambdaS.

Bias↗
PubMed1997

Computation of multilocus prior probability of autozygosity for complex inbred pedigrees.

Homozygosity mapping is a very powerful method for mapping rare recessive diseases in humans. In many applications, it is often desirable to compute prior (or unconditional) multilocus probability of autozygosity for inbred pedigrees. This paper proposes a simple yet powerful method for computing the prior multilocus autozygosity probability for complex inbred pedigrees. The method has an added feature of providing explicit multilocus autozygosity probability in terms of recombination fractions, if desired. An example is presented to illustrate the method.

Chromosome Mapping↗
PubMed1997

Identification of the human chromosomal region containing the iridogoniodysgenesis anomaly locus by genomic-mismatch scanning.

Genome-mismatch scanning (GMS) is a new method of linkage analysis that rapidly isolates regions of identity between two genomes. DNA molecules from regions of identity by descent from two relatives are isolated based on their ability to form extended mismatch-free heteroduplexes. We have applied this rapid technology to identify the chromosomal region shared by two fifth-degree cousins with autosomal dominant iridogoniodysgenesis anomaly (IGDA), a rare ocular neurocristopathy. Markers on the short arm of human chromosome 6p were recovered, consistent with the results of conventional linkage analysis conducted in parallel, indicating linkage of IGDA to 6p25. Control markers tested on a second human chromosome were not recovered. A GMS error rate of approximately 11% was observed, well within an acceptable range for a rapid, first screening approach, especially since GMS results would be confirmed by family analysis with selected markers from the putative region of identity by descent. These results demonstrate not only the value of this technique in the rapid mapping of human genetic traits, but the first application of GMS to a multicellular organism.

Chromosome Mapping↗
PubMed1997

Fine-scale genetic mapping based on linkage disequilibrium: theory and applications.

Linkage-disequilibrium mapping (LDM) recently has been hailed as a powerful statistical method for fine-scale mapping of disease genes. After reviewing its historical background and methodological development, we present a general, mathematical, and conceptually coherent framework for LDM that incorporates multilocus and multiallelic markers and mutational processes at the marker and disease loci. With this framework, we address several issues relevant to fine-scale mapping and propose some efficient computational methods for LDM. We implement various LDM methods that incorporate population growth, recurrent mutation, and marker mutations, on the basis of a general framework. We demonstrate these methods by applying them to published data on cystic fibrosis, Huntington disease, Friedreich ataxia, and progressive myoclonus epilepsy. Since the genes responsible for these diseases all have been cloned, we can evaluate the performance of our methods and can compare ours with that of other methods. Using the proposed methods, we successfully and accurately predicted the locations of genes responsible for these diseases, on the basis of published data only.

Chromosome Mapping↗
PubMed1997

Fine-scale mapping of quantitative trait loci using historical recombinations.

With increasing popularity of QTL mapping in economically important animals and experimental species, the need for statistical methodology for fine-scale QTL mapping becomes increasingly urgent. The ability to disentangle several linked QTL depends on the number of recombination events. An obvious approach to increase the recombination events is to increase sample size, but this approach is often constrained by resources. Moreover, increasing the sample size beyond a certain point will not further reduce the length of confidence interval for QTL map locations. The alternative approach is to use historical recombinations. We use analytical methods to examine the properties of fine QTL mapping using historical recombinations that are accumulated through repeated intercrossing from an F2 population. We demonstrate that, using the historical recombinations, both simple and multiple regression models can reduce significantly the lengths of support intervals for estimated QTL map locations and the variances of estimated QTL map locations. We also demonstrate that, while the simple regression model using historical recombinations does not reduce the variances of the estimated additive and dominant effects, the multiple regression model does. We further determine the power and threshold values for both the simple and multiple regression models. In addition, we calculate the Kullback-Leibler distance and Fisher information for the simple regression model, in the hope to further understand the advantages and disadvantages of using historical recombinations relative to F2 data.

Algorithms↗
PubMed1997

Evidence for two psoriasis susceptibility loci (HLA and 17q) and two novel candidate regions (16q and 20p) by genome-wide scan.

In a 12.5 cM genome-wide scan for psoriasis susceptibility loci, recombination-based tests revealed linkage to the HLA region (Zmax = 3.52), as well as suggestive linkage to two novel regions: chromosome 16q (60-83.1 cM from pter, Zmax = 2.50), and chromosome 20p (7.5-25 cM from pter, Zmax = 2.62). All three regions yielded P values < or = 0.01 by non-parametric analysis. Recombination-based and allele sharing methods also confirmed a previous report of a dominant susceptibility locus on distal chromosome 17q (108.2 cM from pter, Zmax = 2.09, GENEHUNTER P = 0.0056). We could not confirm a previously reported locus on distal chromosome 4q; however, a broad region of unclear significance was identified proximal to this proposed locus (153.6-178.4 cM from pter, Zmax = 1.01). Taken together with our recent results demonstrating linkage to HLA-B and -C, this genome-wide scan identifies a psoriasis susceptibility locus at HLA, confirms linkage to 17q, and recommends two novel genomic regions for further scrutiny. One of these regions (16q) overlaps with a recently-identified susceptibility locus for Crohn's disease. Psoriasis is much more common in patients with Crohn's disease than in controls, suggesting that an immunomodulatory locus capable of influencing both diseases may reside in this region.

Adult↗
PubMed1996

Affected-sib-pair interval mapping and exclusion for complex genetic traits: sampling considerations.

We describe an extension of Risch's [(1990a,b) Am J Hum Genet 46:222-228, 229-241] method of linkage detection and exclusion for complex genetic traits. The method uses interval mapping to infer disease locus identity-by-descent (IBD) sharing for affected sib pairs (ASPs) based on marker information for the ASP and other genotyped family members. The method is likelihood based, and makes use of Risch's parameterization in terms of recurrence risk ratios for relatives. We describe specific linkage detection and exclusion tests for use as genome screening tools to prioritize genomic regions for further study. We also examine issues of optimal study design. We advocate initially typing a large panel of ASPs (and no additional family members) with a map of genetic markers evenly spaced at 10-20-cM intervals. We recommend a screening procedure that 1) investigates further all regions with maximum lod scores greater than 1 and 2) excludes from consideration those regions that result in lod scores less than -2 at the smallest genetic effect that is viewed as important to detect. Further investigation of an interval might include typing other available families or family members, typing additional markers in the interval, and carrying out further statistical analyses. This strategy is efficient in the number of genotypings required and focuses attention on regions most likely to harbor a disease gene with a substantial impact on disease risk, while resulting in the pursuit of a manageable number of false-positive linkage results. Modification may be required if insufficient ASPs are available or if families come from a significantly admixed population.

Chromosome Mapping↗
PubMed1996

Statistical methods for gene map construction by fluorescence in situ hybridization.

Fluorescence in situ hybridization (FISH) provides an efficient and powerful technique for ordering loci both on metaphase chromosomes and in less condensed interphase chromatin. Two-color metaphase FISH can be used to order pairs of loci relative to the centromere; two- and three-color interphase FISH can be used to accurately order trios of loci spaced within 1 Mb relative to one another. Loci separated by a distance > 1-2 Mb exhibit chromatin loops that often give rise to a statistically significant but incorrect order. We derive Bayesian methods for selecting the best locus order based on microscopic evaluation for each of these types of FISH mapping data. We then describe how the results from several two- and three-locus analyses can be combined to evaluate the approximate posterior probability of a given multilocus order within the limits of the technology utilized. These methods directly address the question of interest: What is the probability that the inferred two-, three-, or multilocus order actually is correct? We illustrate our analysis methods by applying them to previously described FISH mapping data of 14 markers in the BRCA1 region on chromosome 17q12-q21. We also propose design strategies to order a group of closely spaced (< 1 Mb) loci, two and three loci at a time, using a bisection strategy for two-color FISH data and a trisection strategy for three-color FISH data. These strategies have the best worst-case performance for ordering a new locus relative to a group of ordered loci and are nearly optimal for ordering a group of loci of unknown order. These, in conjunction with physical mapping strategies, provide efficient and reliable methods for gene map construction by FISH.

BRCA1 Protein↗