969 resultados para False discovery rate
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Copy number variations (CNVs) affect a wide range of phenotypic traits; however, CNVs in or near segmental duplication regions are often intractable. Using a read depth approach based on next-generation sequencing, we examined genome-wide copy number differences among five taurine (three Angus, one Holstein, and one Hereford) and one indicine (Nelore) cattle. Within mapped chromosomal sequence, we identified 1265 CNV regions comprising similar to 55.6-Mbp sequence-476 of which (similar to 38%) have not previously been reported. We validated this sequence-based CNV call set with array comparative genomic hybridization (aCGH), quantitative PCR (qPCR), and fluorescent in situ hybridization (FISH), achieving a validation rate of 82% and a false positive rate of 8%. We further estimated absolute copy numbers for genomic segments and annotated genes in each individual. Surveys of the top 25 most variable genes revealed that the Nelore individual had the lowest copy numbers in 13 cases (similar to 52%, chi(2) test; P-value <0.05). In contrast, genes related to pathogen- and parasite-resistance, such as CATHL4 and ULBP17, were highly duplicated in the Nelore individual relative to the taurine cattle, while genes involved in lipid transport and metabolism, including APOL3 and FABP2, were highly duplicated in the beef breeds. These CNV regions also harbor genes like BPIFA2A (BSP30A) and WC1, suggesting that some CNVs may be associated with breed-specific differences in adaptation, health, and production traits. By providing the first individualized cattle CNV and segmental duplication maps and genome-wide gene copy number estimates, we enable future CNV studies into highly duplicated regions in the cattle genome.
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An artificial neural network (ANN) approach is proposed for the detection of workpiece `burn', the undesirable change in metallurgical properties of the material produced by overly aggressive or otherwise inappropriate grinding. The grinding acoustic emission (AE) signals for 52100 bearing steel were collected and digested to extract feature vectors that appear to be suitable for ANN processing. Two feature vectors are represented: one concerning band power, kurtosis and skew; and the other autoregressive (AR) coefficients. The result (burn or no-burn) of the signals was identified on the basis of hardness and profile tests after grinding. The trained neural network works remarkably well for burn detection. Other signal-processing approaches are also discussed, and among them the constant false-alarm rate (CFAR) power law and the mean-value deviance (MVD) prove useful.
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We develop a general model for adaptive c, np, u and p control charts in which one, two or three design parameters (sample size, sampling interval and control limit width) switch between two values, according to the most recent process information. For a given in-control average sampling rate and a given false alarm rate, the adaptive chart detects changes in the process much faster than a chart with fixed parameters. Moreover, this study also offers general guidance on how to choose an effective design.
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This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding processes. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 Steel as work material. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system working at 2.5 MHz was used to collect the raw acoustic emission instead of the root mean square value usually employed. Many statistical analyses have shown to be effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm rate (CFAR), ratio of power (ROP) and mean-value deviance (MVD). However, the CFAR, ROP, Kurtosis and correlation of the AE have been presented more sensitive than the RMS. Copyright © 2006 by ABCM.
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Background: We evaluated the presence of ductal carcinoma in situ (DCIS) in core needle biopsies (CNB) from invasive ductal lesions. Methods: Retrospective study, which analyzed 90 cases of invasive ductal carcinoma lesions. The percentage of DCIS was quantified in each specimens obtained from CNB, which were compared to the surgical specimens. CNB and surgical specimens were evaluated by the same pathologist, and the percentage of DCIS in CNB was evaluated (percentage) and divided into categories. We considered the following parameters regarding the amount of DCIS: 1 = 0; 2 = 1 for 5%; 3 = 6 for 24%; 4 = 25 for 50%; 5 = 51 for 75% and 6 = 76 for 99%. The number of fragments and the histological pattern of DCIS was found. Results: We found the following results regarding the distribution of the percentage of DCIS in the CNB: 1 = 63.3%; 2 = 12.2%; 3 = 12.2%; 4 = 5.6%; 5 = 1.1% and 6 = 5.6%. The logistic regression analysis showed that CNB percentages above 45% reflected the presence of DCIS in the surgical specimen in 100% of the cases (p<0.001), with a specificity of 100%, accuracy of 83.3% and false positive rate of 0% (p <0.001). Conclusion: There is direct relationship between extensive intraductal component in the surgical specimen when the core biopsy shows 45% or more of the DCI or microinvasive in the material examined. © 2012 Barbalaco Neto et al.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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We present results of a search for continuously emitted gravitational radiation, directed at the brightest low-mass x-ray binary, Scorpius X-1. Our semicoherent analysis covers 10 days of LIGO S5 data ranging from 50-550 Hz, and performs an incoherent sum of coherent F-statistic power distributed amongst frequency-modulated orbital sidebands. All candidates not removed at the veto stage were found to be consistent with noise at a 1% false alarm rate. We present Bayesian 95% confidence upper limits on gravitational-wave strain amplitude using two different prior distributions: a standard one, with no a priori assumptions about the orientation of Scorpius X-1; and an angle-restricted one, using a prior derived from electromagnetic observations. Median strain upper limits of 1.3 x 10(-24) and 8 x 10(-25) are reported at 150 Hz for the standard and angle-restricted searches respectively. This proof-of-principle analysis was limited to a short observation time by unknown effects of accretion on the intrinsic spin frequency of the neutron star, but improves upon previous upper limits by factors of similar to 1.4 for the standard, and 2.3 for the angle-restricted search at the sensitive region of the detector.
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Despite the efficacy of minutia-based fingerprint matching techniques for good-quality images captured by optical sensors, minutia-based techniques do not often perform so well on poor-quality images or fingerprint images captured by small solid-state sensors. Solid-state fingerprint sensors are being increasingly deployed in a wide range of applications for user authentication purposes. Therefore, it is necessary to develop new fingerprint-matching techniques that utilize other features to deal with fingerprint images captured by solid-state sensors. This paper presents a new fingerprint matching technique based on fingerprint ridge features. This technique was assessed on the MSU-VERIDICOM database, which consists of fingerprint impressions obtained from 160 users (4 impressions per finger) using a solid-state sensor. The combination of ridge-based matching scores computed by the proposed ridge-based technique with minutia-based matching scores leads to a reduction of the false non-match rate by approximately 1.7% at a false match rate of 0.1%. © 2005 IEEE.
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We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.
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Background: Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS. Methods: We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer. Results: Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [p(trend)] = 2.5 x 10(-3)). The combined OR for having one additional rare allele was 0.83 (95% CI: 0.76-0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found. Conclusion: This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url: http://services.gate.ac.uk/lld/gwas/service/config).
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Purpose: To validate a monitoring questionnaire about hearing and language development applied by community health agents in the first year of life. Methods: Seventy six community health agents, previously trained on infant hearing health, administered a questionnaire to the families of 304 children with ages from 0 to 1 year. The questionnaire contains questions regarding hearing and language development and, for all age groups, the question “Does your child hear well?” was presented. The validity of the questionnaire was assessed by analyzing false positive and false negative rates of the identified children. A double-blind study was conducted so that all children assessed by the questionnaire were submitted to hearing evaluation performed by audiologists. Results: Four children (1.32%) were diagnosed with sensorineural hearing loss (two unilateral), and 69 (22.7%) with conductive hearing loss. The monitoring questionnaire showed specificity of 96% and sensitivity of 67%, with a false-negative rate of 33% for not identifying the unilateral hearing loss, and a false-positive rate of 4%. Conclusion: The questionnaire used has shown to be feasible and relevant to actions of the community health agents of the Family Health Strategy program, with high specificity and moderate sensitivity. The use of the validated instrument should be considered to complement Newborn Hearing Screening Programs, in order to identify late onset or acquired hearing loss.
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[EN]In this paper, we experimentally study the combination of face and facial feature detectors to improve face detection performance. The face detection problem, as suggeted by recent face detection challenges, is still not solved. Face detectors traditionally fail in large-scale problems and/or when the face is occluded or di erent head rotations are present. The combination of face and facial feature detectors is evaluated with a public database. The obtained results evidence an improvement in the positive detection rate while reducing the false detection rate. Additionally, we prove that the integration of facial feature detectors provides useful information for pose estimation and face alignment.
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Purpose: to quantify the mRNA levels of MMP-3, MMP-9, VEGF and Survivin in peripheral blood and the serum levels of CA-125, Ca19-9 in women with and without endometriosis and to investigate the performance of these markers to differentiate between deep and ovarian endometriosis. Methods: a case controls study enrolled a series of 60 patients. Twenty controls have been matched with 20 cases of ovarian and 20 cases of deep endometriosis. Univariable and multivariable performance of serum CA125 and CA19-9, mRNA for Survivin, MMP9, MMP3 and VEGF genes have been evaluated by means of ROC curves and logistic regression respectively. Results: No difference in markers concentration were detected between ovarian and deep endometriosis. In comparison with controls serum CA19 and CA125 yielded the better sensitivity followed by mRNA for Survivin gene (81.5%, 51.9% and 7.5% at 10% false positive rate respectively). Multivariable estimated odds of endometriosis yielded a sensitivity of 87% at the same false positive rate. Conclusions: A combination of serum and molecular markers could allow a better diagnosis of endometriosis.