Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

BACKGROUND: An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. RESULTS: We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. CONCLUSION: Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site

A reliable measure of similarity based on dependency for short time series: an application to gene expression networks

Abstract Background Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges. Results The results shown here are for an adapted subset of aSaccharomyces cerevisiaegene expression data set with low temporal resolution and poor statistics. The method reveals common transcription factors with a high confidence level and allows the construction of subnetworks with high biological relevance that reveals characteristic features of the processes driving the organism adaptations to specific environmental conditions. Conclusion Our method allows a reliable and sophisticated analysis of microarray data even under severe constraints. The utilization of systems biology improves the biologists ability to elucidate the mechanisms underlying celular processes and to formulate new hypotheses

Prevalence of fibromyalgia in a low socioeconomic status population

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to estimate the prevalence of fibromyalgia, as well as to assess the major symptoms of this syndrome in an adult, low socioeconomic status population assisted by the primary health care system in a city in Brazil.</p> <p>Methods</p> <p>We cross-sectionally sampled individuals assisted by the public primary health care system (n = 768, 35–60 years old). Participants were interviewed by phone and screened about pain. They were then invited to be clinically assessed (304 accepted). Pain was estimated using a Visual Analogue Scale (VAS). Fibromyalgia was assessed using the Fibromyalgia Impact Questionnaire (FIQ), as well as screening for tender points using dolorimetry. Statistical analyses included Bayesian Statistics and the Kruskal-Wallis Anova test (significance level = 5%).</p> <p>Results</p> <p>From the phone-interview screening, we divided participants (n = 768) in three groups: No Pain (NP) (n = 185); Regional Pain (RP) (n = 388) and Widespread Pain (WP) (n = 106). Among those participating in the clinical assessments, (304 subjects), the prevalence of fibromyalgia was 4.4% (95% confidence interval [2.6%; 6.3%]). Symptoms of pain (VAS and FIQ), feeling well, job ability, fatigue, morning tiredness, stiffness, anxiety and depression were statically different among the groups. In multivariate analyses we found that individuals with FM and WP had significantly higher impairment than those with RP and NP. FM and WP were similarly disabling. Similarly, RP was no significantly different than NP.</p> <p>Conclusion</p> <p>Fibromyalgia is prevalent in the low socioeconomic status population assisted by the public primary health care system. Prevalence was similar to other studies (4.4%) in a more diverse socioeconomic population. Individuals with FM and WP have significant impact in their well being.</p

HIV Aspartyl Peptidase Inhibitors Interfere with Cellular Proliferation, Ultrastructure and Macrophage Infection of Leishmania amazonensis

Submitted by Sandra Infurna ([email protected]) on 2019-01-08T13:43:09Z No. of bitstreams: 1 Ellenf_Altoe_etal_IOC_2009.pdf: 1452755 bytes, checksum: 77127a59920cef6bca71296107f6ec63 (MD5)Approved for entry into archive by Sandra Infurna ([email protected]) on 2019-01-08T13:51:34Z (GMT) No. of bitstreams: 1 Ellenf_Altoe_etal_IOC_2009.pdf: 1452755 bytes, checksum: 77127a59920cef6bca71296107f6ec63 (MD5)Made available in DSpace on 2019-01-08T13:51:34Z (GMT). No. of bitstreams: 1 Ellenf_Altoe_etal_IOC_2009.pdf: 1452755 bytes, checksum: 77127a59920cef6bca71296107f6ec63 (MD5) Previous issue date: 2009Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Molecular e Doenças Endêmicas. Rio de Janeiro, RJ. Brasil.Universidade Federal do Rio de Janeiro. Centro de Ciências da Saúde. Instituto de Microbiologia Prof. Paulo de Góes. Departamento de Microbiologia Geral,. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Molecular e Doenças Endêmicas. Rio de Janeiro, RJ. Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Molecular e Doenças Endêmicas. Rio de Janeiro, RJ. Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Molecular e Doenças Endêmicas. Rio de Janeiro, RJ. Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Molecular e Doenças Endêmicas. Rio de Janeiro, RJ. Brasil.Universidade Federal do Rio de Janeiro. Centro de Ciências da Saúde. Instituto de Biofísica Carlos Chagas Filho. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Centro de Ciências da Saúde. Instituto de Microbiologia Prof. Paulo de Góes. Departamento de Microbiologia Geral,. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Centro de Ciências da Saúde. Instituto de Microbiologia Prof. Paulo de Góes. Departamento de Microbiologia Geral,. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Molecular e Doenças Endêmicas. Rio de Janeiro, RJ. Brasil.Leishmania is the etiologic agent of leishmanisais, a protozoan disease whose pathogenic events are not well understood. Current therapy is suboptimal due to toxicity of the available therapeutic agents and the emergence of drug resistance. Compounding these problems is the increase in the number of cases of Leishmania-HIV coinfection, due to the overlap between the AIDS epidemic and leishmaniasis