38 resultados para Error-location numbers
Resumo:
The choice of genotyping families vs unrelated individuals is a critical factor in any large-scale linkage disequilibrium (LD) study. The use of unrelated individuals for such studies is promising, but in contrast to family designs, unrelated samples do not facilitate detection of genotyping errors, which have been shown to be of great importance for LD and linkage studies and may be even more important in genotyping collaborations across laboratories. Here we employ some of the most commonly-used analysis methods to examine the relative accuracy of haplotype estimation using families vs unrelateds in the presence of genotyping error. The results suggest that even slight amounts of genotyping error can significantly decrease haplotype frequency and reconstruction accuracy, that the ability to detect such errors in large families is essential when the number/complexity of haplotypes is high (low LD/common alleles). In contrast, in situations of low haplotype complexity (high LD and/or many rare alleles) unrelated individuals offer such a high degree of accuracy that there is little reason for less efficient family designs. Moreover, parent-child trios, which comprise the most popular family design and the most efficient in terms of the number of founder chromosomes per genotype but which contain little information for error detection, offer little or no gain over unrelated samples in nearly all cases, and thus do not seem a useful sampling compromise between unrelated individuals and large families. The implications of these results are discussed in the context of large-scale LD mapping projects such as the proposed genome-wide haplotype map.
Resumo:
Objective: To describe new measures of risk from case-control and cohort studies, which are simple to understand and relate to numbers of the population at risk. Design: Theoretical development of new measures of risk. Setting: Review of literature and previously described measures. Main results: The new measures are: (1) the population impact number (PIN), the number of those in the whole population among whom one case is attributable to the exposure or risk factor (this is equivalent to the reciprocal of the population attributable risk),- (2) the case impact number (CIN) the number of people with the disease or outcome for whom one case will be attributable to the exposure or risk factor (this is equivalent to the reciprocal of the population attributable fraction); (3) the exposure impact number (EIN) the number of people with the exposure among whom one excess case is attributable to the exposure (this is equivalent to the reciprocal of the attributable risk); (4) the exposed cases impact number (ECIN) the number of exposed cases among whom one case is attributable to the exposure (this is equivalent to the reciprocal of the aetiological fraction). The impact number reflects the number of people in each population (the whole population, the cases, all those exposed, and the exposed cases) among whom one case is attributable to the particular risk factor. Conclusions: These new measures should help communicate the impact on a population, of estimates of risk derived from cohort or case-control studies.
Resumo:
Objective: To outline the major methodological issues appropriate to the use of the population impact number (PIN) and the disease impact number (DIN) in health policy decision making. Design: Review of literature and calculation of PIN and DIN statistics in different settings. Setting: Previously proposed extensions to the number needed to treat (NNT): the DIN and the PIN, which give a population perspective to this measure. Main results: The PIN and DIN allow us to compare the population impact of different interventions either within the same disease or in different diseases or conditions. The primary studies used for relative risk estimates should have outcomes, time periods and comparison groups that are congruent and relevant to the local setting. These need to be combined with local data on disease rates and population size. Depending on the particular problem, the target may be disease incidence or prevalence and the effects of interest may be either the incremental impact or the total impact of each intervention. For practical application, it will be important to use sensitivity analyses to determine plausible intervals for the impact numbers. Conclusions: Attention to various methodological issues will permit the DIN and PIN to be used to assist health policy makers assign a population perspective to measures of risk.
Resumo:
Recent laboratory studies have demonstrated that Prunus necrotic ringspot virus (PNRSV) (family Bromoviridae) can be readily transmitted when thrips and virus-bearing pollen are placed together on to test plants. For this transmission mechanism to result in stonefruit tree infection in the field, PNRSV-bearing pollen must be deposited onto surfaces of stonefruit trees on which thrips also occur. In a previous paper, we demonstrated that almost all pollen in a PNRSV-infected Japanese plum orchard in southeastern Queensland was deposited onto flowers, whereas few grains occurred on leaves and none on stems. Here, we present results of our investigation of thrips species composition, distribution and abundance on stonefruit trees in the same study area as our previous pollen deposition study. We collected a total of 2010 adult thrips from 13 orchards during the 1989, 1991 and 1992 flowering seasons of which all but 14 were in the suborder Terebrantia. Most (97.4%) terebrantian thrips were of three species, Thrips imaginis, Thrips australis and Thrips tabaci. Thrips tabaci as well as species mixtures that included T imaginis, T australis and T tabaci have been shown to transmit PNRSV via infected pollen in laboratory tests. Adult thrips were frequently collected from flowers but rarely from leaves and never from stems. Large and significant differences in numbers of T imaginis, T australis and T tabaci adults in flowers occurred among orchards and between seasons. No factor was conclusively related to thrips numbers but flowers of late-flowering stonefruit varieties tended to hold more thrips than those of early-flowering varieties. Our results indicate that the common thrips species present on stonefruit trees in the Granite Belt are also ones previously shown to transmit PNRSV via infected pollen in the laboratory and that these thrips are concentrated in stonefruit flowers where most stonefruit pollen is deposited. These results contribute to mounting circumstantial evidence that stonefruit flowers may be inoculated with PNRSV via an interaction of thrips with virus-bearing pollen and that this transmission mechanism may be an important cause of new tree infections in the field.
Resumo:
To define the location of potential oncogenes and tumor suppressor genes in ocular melanoma we carried out comparative genomic hybridization (CGH) analysis on a population-based series of 25 formalin-fixed, paraffin-embedded primary tumors comprising 17 choroidal, 2 ciliary body, 4 iris, and 2 conjunctival melanomas. Twelve (48%) of the 25 melanomas showed no chromosomal changes and 13 (52%) had at least one chromosomal gain or loss. The mean number of CGH changes in all tumors was 3.3, with similar mean numbers of chromosomal gains (1.5) and losses (1.8). The highest number of chromosomal changes (i.e., nine) occurred in a conjunctival melanoma and included four changes not observed in tumors at any other ocular site (gains in 22q and 11p and losses in 6p and 17p). The most frequent gains in all primary ocular melanomas were on chromosome arm 8q (69%), 6p (31%) and 8p (23%) and the most frequent losses were on 6q (38%), 10q (23%), and 16q (23%). The most common pairing was gain in 8p and gain in 8q, implying a whole chromosome copy number increase; gains in 8p occurred only in conjunction with gains in 8q. The smallest regions of copy number alteration were mapped to gain of 8q21 and loss of 6q21, 10q21, and 16q22. Sublocalization of these chromosomal changes to single-band resolution should accelerate the identification of genes involved in the genesis of ocular melanoma.
Resumo:
Undemutrition during early life is known to cause deficits and distortions of brain structure although it has remained uncertain whether or not this includes a diminution of the total numbers of neurons. Estimates of numerical density (e.g. number of cells per microscopic field, or number of cells per unit area of section, or number of cells per unit volume of tissue) are extremely difficult to interpret and do not provide estimates of total numbers of cells. However, advances in stereological techniques have made it possible to obtain unbiased estimates of total numbers of cells in well defined biological structures. These methods have been utilised in studies to determine the effects of varying periods of undernutrition during early life on the numbers of neurons in various regions of the rat brain. The regions examined so far have included the cerebellum, the dentate gyrus, the olfactory bulbs and the cerebral cortex. The only region to show, unequivocally, that a period of undernutrition during early life causes a deficit in the number of neurons was the dentate gyrus. These findings are discussed in the context of other morphological and functional deficits present in undernourished animals.