Symbolic Formulae for Linear Mixed Models

A statistical model is a mathematical representation of an often simplified or idealised data-generating process. In this paper, we focus on a particular type of statistical model, called linear mixed models (LMMs), that is widely used in many disciplines e.g.~agriculture, ecology, econometrics, psychology. Mixed models, also commonly known as multi-level, nested, hierarchical or panel data models, incorporate a combination of fixed and random effects, with LMMs being a special case. The inclusion of random effects in particular gives LMMs considerable flexibility in accounting for many types of complex correlated structures often found in data. This flexibility, however, has given rise to a number of ways by which an end-user can specify the precise form of the LMM that they wish to fit in statistical software. In this paper, we review the software design for specification of the LMM (and its special case, the linear model), focusing in particular on the use of high-level symbolic model formulae and two popular but contrasting R-packages in lme4 and asreml

Elevated c-Src is linked to altered cell–matrix adhesion rather than proliferation in KM12C human colorectal cancer cells

Elevated expression and/or activity of c-Src, the prototype of the Src family of protein tyrosine kinases, is associated with the development of human colon cancer. However, despite the known pleiotropic effects of these kinases in promoting (a) cell growth downstream of growth factor receptors, and (b) the dynamic regulation of integrin adhesions in fibroblast model systems, their precise role in epithelial cancer cells is unknown. Here we addressed whether elevated expression and activity of cellular Src alters cell proliferation and/or cell–matrix adhesion in cancer cells from the Fidler model of colorectal metastasis. Although elevated Src correlates with ability to metastasise to the liver after intrasplenic injection, we found that this was not linked to enhanced growth, either in vitro or in vivo as sub-cutaneous tumours. However, elevated Src was associated with enhanced attachment to extracellular matrix. In addition, adhesion to fibronectin, was suppressed by agents that inhibited Src activity, while enforced elevation of Src in non-metastatic cells was sufficient to stimulate adhesion to fibronectin and enhanced assembly of adhesion complexes, without influencing cell growth. Thus, we conclude that one role of elevated Src in human colon cancer cells is to modulate integrin-dependent cell–matrix attachment and formation of adhesion structures, which may, in turn, influence cell motility and integrin-dependent cellular responses

Alterations in LMTK2, MSMB and HNF1B gene expression are associated with the development of prostate cancer

<p>Abstract</p> <p>Background</p> <p>Genome wide association studies (GWAS) have identified several genetic variants that are associated with prostate cancer. Most of these variants, like other GWAS association signals, are located in non-coding regions of potential candidate genes, and thus could act at the level of the mRNA transcript.</p> <p>Methods</p> <p>We measured the expression and isoform usage of seven prostate cancer candidate genes in benign and malignant prostate by real-time PCR, and correlated these factors with cancer status and genotype at the GWAS risk variants.</p> <p>Results</p> <p>We determined that levels of <it>LMTK2 </it>transcripts in prostate adenocarcinomas were only 32% of those in benign tissues (p = 3.2 × 10^-7), and that an independent effect of genotype at variant rs6465657 on <it>LMTK2 </it>expression in benign (n = 39) and malignant tissues (n = 21) was also evident (P = 0.002). We also identified that whilst <it>HNF1B(C) </it>and <it>MSMB2 </it>comprised the predominant isoforms in benign tissues (90% and 98% of total <it>HNF1B </it>or <it>MSMB </it>expression)<it>, HNF1B(B) and MSMB1 </it>were predominant in malignant tissue (95% and 96% of total <it>HNF1B </it>or <it>MSMB </it>expression; P = 1.7 × 10^-7and 4 × 10^-4respectively), indicating major shifts in isoform usage.</p> <p>Conclusions</p> <p>Our results indicate that the amount or nature of mRNA transcripts expressed from the <it>LMTK2</it>, <it>HNF1B </it>and <it>MSMB </it>candidate genes is altered in prostate cancer, and provides further evidence for a role for these genes in this disorder. The alterations in isoform usage we detect highlights the potential importance of alternative mRNA processing and moderation of mRNA stability as potentially important disease mechanisms.</p

Spatial and temporal dynamics of fucoid populations (Ascophyllum nodosum and Fucus serratus): A comparison between central and range edge populations

Persistence of populations at range edges relies on local population dynamics and fitness, in the case of geographically isolated populations of species with low dispersal potential. Focusing on spatial variations in demography helps to predict the long-term capability for persistence of populations across the geographical range of species' distribution. The demography of two ecological and phylogenetically close macroalgal species with different life history characteristics was investigated by using stochastic, stage-based matrix models. Populations of Ascophyllum nodosum and Fucus serratus were sampled for up to 4 years at central locations in France and at their southern range limits in Portugal. The stochastic population growth rate (lambda(s)) of A. nodosum was lower and more variable in central than in southern sites whilst for F. serratus this trend was reversed with lambda(s) much lower and more variable in southern than in central populations. Individuals were larger in central than in southern populations for both species, which was reflected in the lower transition probabilities of individuals to larger size classes and higher probability of shrinkage in the southern populations. In both central and southern populations elasticity analysis (proportional sensitivity) of population growth rate showed that fertility elements had a small contribution to lambda(s) that was more sensitive to changes in matrix transitions corresponding to survival. The highest elasticities were found for loop transitions in A. nodosum and for growth to larger size classes in F. serratus. Sensitivity analysis showed high selective pressure on individual growth for both species at both locations. The results of this study highlight the deterministic role of species-specific life-history traits in population demography across the geographical range of species. Additionally, this study demonstrates that individuals' life-transitions differ in vulnerability to environmental variability and shows the importance of vegetative compared to reproductive stages for the long-term persistence of populations.Portuguese Foundation for Science and Technology (FCT) [SFRH/BPD/75843/2011]; European Regional Development Fund (ERDF) through the COMPETE - Operational Competitiveness Programme; FCT [Pest-CIMAR LA 0015/2013, EXCL/AAG-GLO/0661/2012

The FunGenES Database: A Genomics Resource for Mouse Embryonic Stem Cell Differentiation

Embryonic stem (ES) cells have high self-renewal capacity and the potential to differentiate into a large variety of cell types. To investigate gene networks operating in pluripotent ES cells and their derivatives, the “Functional Genomics in Embryonic Stem Cells” consortium (FunGenES) has analyzed the transcriptome of mouse ES cells in eleven diverse settings representing sixty-seven experimental conditions. To better illustrate gene expression profiles in mouse ES cells, we have organized the results in an interactive database with a number of features and tools. Specifically, we have generated clusters of transcripts that behave the same way under the entire spectrum of the sixty-seven experimental conditions; we have assembled genes in groups according to their time of expression during successive days of ES cell differentiation; we have included expression profiles of specific gene classes such as transcription regulatory factors and Expressed Sequence Tags; transcripts have been arranged in “Expression Waves” and juxtaposed to genes with opposite or complementary expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic resources. The FunGenES database provides a comprehensive resource for studies into the biology of ES cells

Association Testing Of Copy Number Variants in Schizophrenia and Autism Spectrum Disorders

Background: Autism spectrum disorders and schizophrenia have been associated with an overlapping set of copynumber variant loci, but the nature and degree of overlap in copy number variants (deletions compared toduplications) between these two disorders remains unclear.Methods: We systematically evaluated three lines of evidence: (1) the statistical bases for associations of autismspectrum disorders and schizophrenia with a set of the primary CNVs thus far investigated, from previous studies;(2) data from case series studies on the occurrence of these CNVs in autism spectrum disorders, especially amongchildren, and (3) data on the extent to which the CNVs were associated with intellectual disability anddevelopmental, speech, or language delays. We also conducted new analyses of existing data on these CNVs inautism by pooling data from seven case control studies.Results: Four of the CNVs considered, dup 1q21.1, dup 15q11-q13, del 16p11.2, and dup 22q11.21, showed clearstatistical evidence as autism risk factors, whereas eight CNVs, del 1q21.1, del 3q29, del 15q11.2, del 15q13.3, dup16p11.2, dup 16p13.1, del 17p12, and del 22q11.21, were strongly statistically supported as risk factors forschizophrenia. Three of the CNVs, dup 1q21.1, dup 16p11.2, and dup 16p13.1, exhibited statistical support as riskfactors for both autism and schizophrenia, although for each of these CNVs statistical significance was nominal fortests involving one of the two disorders. For the CNVs that were statistically associated with schizophrenia but werenot statistically associated with autism, a notable number of children with the CNVs have been diagnosed withautism or ASD; children with these CNVs also demonstrate a high incidence of intellectual disability anddevelopmental, speech, or language delays.Conclusions: These findings suggest that although CNV loci notably overlap between autism and schizophrenia,the degree of strongly statistically supported overlap in specific CNVs at these loci remains limited. These analysesalso suggest that relatively severe premorbidity to CNV-associated schizophrenia in children may sometimes bediagnosed as autism spectrum disorder