Matrix2png: a utility for visualizing matrix data

We describe a simple software tool, 'matrix2png', for creating color images of matrix data. Originally designed with the display of microarray data sets in mind, it is a general tool that can be used to make simple visualizations of matrices for use in figures, web pages, slide presentations and the like. It can also be used to generate images 'on the fly' in web applications. Both continuous-valued and discrete-valued (categorical) data sets can be displayed. Many options are available to the user, including the colors used, the display of row and column labels, and scale bars. In this note we describe some of matrix2png's features and describe some places it has been useful in the authors' work. AVAILABILITY: A simple web interface is available, and Unix binaries are available from http://microarray.cpmc.columbia.edu/matrix2png. Source code is available on request.     

Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.

Background

Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods.

Results

Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression.

Conclusion

In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects.

     

Using ANOVA for gene selection from microarray studies of the nervous system

Methods are presented for detecting differential expression using statistical hypothesis testing methods including analysis of variance (ANOVA). Practicalities of experimental design, power, and sample size are discussed. Methods for multiple testing correction and their application are described. Instructions for running typical analyses are given in the R programming environment. R code and the sample data set used to generate the examples are available at http://microarray.cpmc.columbia.edu/pavlidis/pub/aovmethods/.     

Temperature sex determination in the European sea bass,Dicentrarchus labrax (L., 1758) (Teleostei,Perciformes, Moronidae): critical sensitive ontogenetic phase

The temperature sex determination (TSD) mechanism in the European sea bass (Dicentrarchus labrax L.) was studied in respect to: a) the TSD sensitivity during the different developmental stages; and b) the intrapopulation correlation of sex determination with the growth rate up to the end of the TSD-sensitive period. At the stage of half-epiboly, eggs from the same batch were divided into four groups and subjected to different thermal treatments: a) 15 degrees C (G15 group) and b) 20 degrees C (G20 group) up to the middle of metamorphosis stage; c) 15 degrees C up to the end of yolk-sac larval stage and subsequently to 20 degrees C (G15-5 group); and d) 15 degrees C up to the end of the preflexion stage and then to 20 degrees C (G15-10 group). At the end of the treatments, size grading was applied and four additional populations were established from the upper (L) and lower (S) size portions of the G15 and G20 populations: G15L, G15S, G20L, and G20S. During the following growing phase, all populations were subjected to common rearing conditions. The sex ratios of each population were macroscopically determined at 190-210 mm mean total length. Female incidence was significantly affected (P < 0.05) by the different thermal treatments: 66.1% in the G15, 47.1% in the G15-10, 37.6% in the G15-5, and 18.1% in the G20 group. In addition, sex ratio was correlated with the growth rate of the fish up to the end of the TSD-sensitive period, with the larger fish presenting a significantly higher (P < 0.01) female incidence than the smaller fish in both thermal regimes tested: 73.1% in G15L vs. 57% in G15S, and 36.6% in G20L vs. 22.5% in G20S group. Results provide, for the first time, clear evidence that the sea bass is sensitive to TSD during all different ontogenetic stages up to metamorphosis, and that sex ratio is correlated with the growth rate of the fish well before the differentiation and maturation of the gonads.     

Characterization and Expression Dynamics of Key Genes Involved in the Gilthead Sea Bream (<Emphasis Type="Italic">Sparus aurata</Emphasis>) Cortisol Stress Response during Early Ontogeny

The present study identified and characterized six key genes involved in the hypothalamic-pituitary-interrenal (HPI) axis of gilthead sea bream (Sparus aurata), a commercially important European aquaculture species. The key genes involved in the HPI axis for which gene structure and synteny analysis was carried out, comprised of two functional forms of glucocorticoid receptors (GR), as well as three forms of pro-opiomelanocortin (POMC) genes and one form of mineralocorticoid receptor (MR) gene. To explore their functional roles during development but also in the stress response, the expression profiles of gr1, gr2, mr, pomc_aI, pomc_aII, and pomc_β were examined during early ontogeny and after an acute stress challenge. The acute stress challenge was applied at the stage of full formation of all fins, where whole body cortisol was also measured. Both the cortisol and the molecular data implied that sea bream larvae at the stage of the full formation of all fins at 45 dph are capable of a response to stress of a similar profile as observed in adult fish.     

Decoding unattended fearful faces with whole-brain correlations: an approach to identify condition-dependent large-scale functional connectivity

Processing of unattended threat-related stimuli, such as fearful faces, has been previously examined using group functional magnetic resonance (fMRI) approaches. However, the identification of features of brain activity containing sufficient information to decode, or "brain-read", unattended (implicit) fear perception remains an active research goal. Here we test the hypothesis that patterns of large-scale functional connectivity (FC) decode the emotional expression of implicitly perceived faces within single individuals using training data from separate subjects. fMRI and a blocked design were used to acquire BOLD signals during implicit (task-unrelated) presentation of fearful and neutral faces. A pattern classifier (linear kernel Support Vector Machine, or SVM) with linear filter feature selection used pair-wise FC as features to predict the emotional expression of implicitly presented faces. We plotted classification accuracy vs. number of top N selected features and observed that significantly higher than chance accuracies (between 90-100%) were achieved with 15-40 features. During fearful face presentation, the most informative and positively modulated FC was between angular gyrus and hippocampus, while the greatest overall contributing region was the thalamus, with positively modulated connections to bilateral middle temporal gyrus and insula. Other FCs that predicted fear included superior-occipital and parietal regions, cerebellum and prefrontal cortex. By comparison, patterns of spatial activity (as opposed to interactivity) were relatively uninformative in decoding implicit fear. These findings indicate that whole-brain patterns of interactivity are a sensitive and informative signature of unattended fearful emotion processing. At the same time, we demonstrate and propose a sensitive and exploratory approach for the identification of large-scale, condition-dependent FC. In contrast to model-based, group approaches, the current approach does not discount the multivariate, joint responses of multiple functional connections and is not hampered by signal loss and the need for multiple comparisons correction.     

Network Analyses Reveal Pervasive Functional Regulation Between Proteases in the Human Protease Web

Proteolytic processing is an irreversible posttranslational modification affecting a large portion of the proteome. Protease-cleaved mediators frequently exhibit altered activity, and biological pathways are often regulated by proteolytic processing. Many of these mechanisms have not been appreciated as being protease-dependent, and the potential in unraveling a complex new dimension of biological control is increasingly recognized. Proteases are currently believed to act individually or in isolated cascades. However, conclusive but scattered biochemical evidence indicates broader regulation of proteases by protease and inhibitor interactions. Therefore, to systematically study such interactions, we assembled curated protease cleavage and inhibition data into a global, computational representation, termed the protease web. This revealed that proteases pervasively influence the activity of other proteases directly or by cleaving intermediate proteases or protease inhibitors. The protease web spans four classes of proteases and inhibitors and so links both recently and classically described protease groups and cascades, which can no longer be viewed as operating in isolation in vivo. We demonstrated that this observation, termed reachability, is robust to alterations in the data and will only increase in the future as additional data are added. We further show how subnetworks of the web are operational in 23 different tissues reflecting different phenotypes. We applied our network to develop novel insights into biologically relevant protease interactions using cell-specific proteases of the polymorphonuclear leukocyte as a system. Predictions from the protease web on the activity of matrix metalloproteinase 8 (MMP8) and neutrophil elastase being linked by an inactivating cleavage of serpinA1 by MMP8 were validated and explain perplexing Mmp8 ^−/− versus wild-type polymorphonuclear chemokine cleavages in vivo. Our findings supply systematically derived and validated evidence for the existence of the protease web, a network that affects the activity of most proteases and thereby influences the functional state of the proteome and cell activity.