44 research outputs found

    J Comput Biol

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    Gene expression measurements allow determining sets of up- or down-regulated, or unchanged genes in a particular experimental condition. Additional biological knowledge can suggest examples of genes from one of these sets. For instance, known target genes of a transcriptional activator are expected, but are not certain to go down after this activator is knocked out. Available differential expression analysis tools do not take such imprecise examples into account. Here we put forward a novel partially supervised mixture modeling methodology for differential expression analysis. Our approach, guided by imprecise examples, clusters expression data into differentially expressed and unchanged genes. The partially supervised methodology is implemented by two methods: a newly introduced belief-based mixture modeling, and soft-label mixture modeling, a method proved efficient in other applications. We investigate on synthetic data the input example settings favorable for each method. In our tests, both belief-based and soft-label methods prove their advantage over semi-supervised mixture modeling in correcting for erroneous examples. We also compare them to alternative differential expression analysis approaches, showing that incorporation of knowledge yields better performance. We present a broad range of knowledge sources and data to which our partially supervised methodology can be applied. First, we determine targets of Ste12 based on yeast knockout data, guided by a Ste12 DNA-binding experiment. Second, we distinguish miR-1 from miR-124 targets in human by clustering expression data under transfection experiments of both microRNAs, using their computationally predicted targets as examples. Finally, we utilize literature knowledge to improve clustering of time-course expression profiles

    Why Y chromosome is shorter and women live longer?

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    We have used the Penna ageing model to analyze how the differences in evolution of sex chromosomes depend on the strategy of reproduction. In panmictic populations, when females (XX) can freely choose the male partner (XY) for reproduction from the whole population, the Y chromosome accumulates defects and eventually the only information it brings is a male sex determination. As a result of shrinking Y chromosome the males become hemizygous in respect to the X chromosome content and are characterized by higher mortality, observed also in the human populations. If it is assumed in the model that the presence of the male is indispensable at least during the pregnancy of his female partner and he cannot be seduced by another female at least during the one reproduction cycle - the Y chromosome preserves its content, does not shrink and the lifespan of females and males is the same. Thus, Y chromosome shrinks not because of existing in one copy, without the possibility of recombination, but because it stays under weaker selection pressure; in panmictic populations without the necessity of being faithful, a considerable fraction of males is dispensable and they can be eliminated from the population without reducing its reproduction potential.Comment: 8 pages, 5 figure

    intsvy: An R package for analysing International large-scale assessment data

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    This paper introduces intsvy, an R package for working with international assessment data (e.g. PISA, TIMSS, PIRLS). The package includes functions for importing data, performing data analysis, and visualising results. The paper describes the underlying methodology and provides real data examples. Tools for importing data allow useRs to select variables from student, home, school, and teacher survey instruments as well as for specific countries. Data analysis functions take into account the complex sample design (with replicate weights) and rotated test forms (with plausible achievement values) in the calculation of point estimates and standard errors of means, standard deviations, regression coefficients, correlation coefficients, and frequency tables. Visualisation tools present data aggregates in standardised graphical form

    Prognostic Role of Tumoral PD-L1 and IDO1 Expression, and Intratumoral CD8+ and FoxP3+ Lymphocyte Infiltrates in 132 Primary Cutaneous Merkel Cell Carcinomas

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    The association of immune markers and clinicopathologic features and patient outcome has not been extensively studied in Merkel cell carcinoma (MCC). We correlated tumoral PD-L1 and IDO1 expression, and intratumoral CD8+ and FoxP3+ lymphocytes count with clinicopathologic variables, Merkel cell polyomavirus (MCPyV) status, and patient outcomes in a series of 132 MCC. By univariate analyses, tumoral PD-L1 expression >1% and combined tumoral PD-L1 >1% and high intratumoral FoxP3+ lymphocyte count correlated with improved overall survival (OS) (p = 0.016, 0.0072), MCC-specific survival (MSS) (p = 0.019, 0.017), and progression-free survival (PFS) (p = 0.043, 0.004, respectively). High intratumoral CD8+ and FoxP3+ lymphocyte count correlated with longer MSS (p = 0.036) and improved PFS (p = 0.047), respectively. Ulceration correlated with worse OS and worse MSS. Age, male gender, and higher stage (3 and 4) significantly correlated with worse survival. MCPyV positivity correlated with immune response. By multivariate analyses, only ulceration and age remained as independent predictors of worse OS; gender and stage remained for shorter PFS. Tumoral PD-L1 expression and increased density of intratumoral CD8+ lymphocytes and FoxP+ lymphocytes may represent favorable prognosticators in a subset of MCCs. Tumoral PD-L1 expression correlated with intratumoral CD8+ and FoxP3+ lymphocytes, which is supportive of an adaptive immune response
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