Statistical Methods for Differential Expressions of Genes Detected in Multiple-Condition Experiment of Microarray

Most studies of differential gene-expressions have been conducted between two given conditions. The two-condition experimental (TCE) approach is simple in that all genes detected display a common differential expression pattern responsive to a common two-condition difference. Therefore, the genes that are differentially expressed under the other conditions other than the given two conditions are undetectable with the TCE approach. In order to address the problem, we propose a new approach called multiple-condition experiment (MCE) without replication and develop corresponding statistical methods including inference of pairs of conditions for genes, new t-statistics, and a generalized multiple-testing method for any multiple-testing procedure via a control parameter C. We applied these statistical methods to analyze our real MCE data from breast cancer cell lines and found that 85 percent of gene-expression variations were caused by genotypic effects and genotype-ANAX1 overexpression interactions, which agrees well with our expected results. We also applied our methods to the adenoma dataset of Notterman et al. and identified 93 differentially expressed genes that could not be found in TCE. The MCE approach is a conceptual breakthrough in many aspects: (a) many conditions of interests can be conducted simultaneously; (b) study of association between differential expressions of genes and conditions becomes easy; (c) it can provide more precise information for molecular classification and diagnosis of tumors; (d) it can save lot of experimental resources and time for investigators.^

InGen of creative production in the health sciences: A workbook companion to innovation generation

InGen of Creative Production in the Health Sciences is a compendium of innovative thinking exercises for individuals and groups, derived from an eclectic array of practical guides for professionals in a variety of fields. Segmented into five subcategories across twenty two chapters, the effort seeks to make techniques for increasing innovative problem solving more accessible to a diverse audience of problem solvers. The chapters of Roberta Ness. Innovation Generation (2012, Oxford University Press) provide the themes for each of the chapters in the workbook. It is intended that those who read Ness. Innovation Generation will benefit from practicing the constructs of innovative thinking exemplified in each exercise.^ The methods used to gather data, in this case mostly innovative thinking exercises, included literature reviews of existing innovative thinking tools, classroom materials, and theory-driven exploration of exercises to fill in gaps in extant materials. Specifically, Google.com and Amazon.com searches were conducted using the terms “innovation,” “innovative,” “innovator,” “creative,” “novelty,” “thinking,” together with some variance of “book,” “workbook,” and “exercise.” The results were sorted thematically to show correspondence with the themes in Ness (2012) and compared to suggested best practices of 50 years of scientific research on innovative thinking. Where themes were suggested by Ness (2012) and peer-reviewed research on innovation but unavailable in published innovation thinking workbooks, new exercises were developed. The five type subcategories into which these results were organized are: individual direct, individual indirect, group direct, group indirect and probing question. It is anticipated that the five type subcategories and spectrum of themes will equip problem solvers in a variety of capacities.^