Statistical Analysis Module Research Articles

MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation.

We introduce MetaboAnalyst version 6.0 as a unified platform for processing, analyzing, and interpreting data from targeted as well as untargeted metabolomics studies using liquid chromatography - mass spectrometry (LC-MS). The two main objectives in developing version 6.0 are to support tandem MS (MS2) data processing and annotation, as well as to support the analysis of data from exposomics studies and related experiments. Key features of MetaboAnalyst 6.0 include: (i) a significantly enhanced Spectra Processing module with support for MS2 data and the asari algorithm; (ii) a MS2 Peak Annotation module based on comprehensive MS2 reference databases with fragment-level annotation; (iii) a new Statistical Analysis module dedicated for handling complex study design withmultiple factors orphenotypic descriptors; (iv) a Causal Analysis module for estimating metabolite - phenotype causal relations based on two-sample Mendelian randomization,and (v) a Dose-Response Analysis module for benchmark dose calculations. In addition, we have also improved MetaboAnalyst's visualization functions, updated its compound database and metabolite sets, and significantly expanded its pathway analysis support to around 130 species. MetaboAnalyst 6.0 is freely available at https://www.metaboanalyst.ca.

Design and Application of Medical Equipment Management System Based on B/S Architecture and WeChat Official Accounts

In order to solve the problems of equipment comprehensive management in grade A hospitals, such as complicated work, low maintenance efficiency, error-prone, non-standard management process, et al. A set of efficient information-based medical management equipment platform was designed to serve the concept of medical departments. B/S (browser and server) architecture and WeChat official accounts technology were adopted to construct the application end and WeChat official accounts client developed by Web technology, and MySQL server was selected as the system database technology. Asset management, equipment maintenance, quality control management, equipment leasing, data statistical analysis and other modules were integrated into the system, which optimized and standardized the medical equipment management process, improved the work efficiency of equipment management personnel, and improved the opening rate of medical equipment. Intelligent management by means of computer technology can effectively improve the utilization rate of hospital equipment, improve the level of hospital informatization and fine management, and contribute to the informatization development of medical engineering department.

TMIC-30. EFFICIENT, QUANTITATIVE MAPPING OF TUMOR-IMMUNE NEIGHBORHOOD COMPOSITION IN GLIOBLASTOMA USING CASSATT

Abstract The microenvironment surrounding brain cancer cells, and their position relative to anatomical features such as the vasculature, is a critical contributor to tumor malignancy. Immunohistochemical staining is widely used to examine such multicellular interactions, and approaches like cyclic immunohistochemistry (cycIHC), multiplexed immunofluorescence, or mass-based imaging can include up to 100 channels of interest. However, large (often > 50 GB) datasets from cycIHC or comparable approaches currently require an expert data scientist to concatenate open-source tools for each step of image pre-processing, registration, and segmentation, or the use of expensive proprietary software. We generated an open-source, unified, and user-friendly workflow for processing and analyzing cycIHC data - Cyclic Analysis of Single-Cell Subsets and Tissue Territories (CASSATT). CASSATT registers scanned slide images across all rounds of staining, segments individual nuclei, and scores marker expression on each detected cell. Beyond straightforward data analysis outputs such as dimensionality reduction, clustering, cell population identification and quantification, CASSATT explores the spatial relationships between cell populations via a statistical analysis module that can be applied to other high-dimensional imaging data types. In brief, it helps users identify populations of cells that interact - or do not interact - at frequencies that are greater than those occurring by chance. It also identifies specific ‘neighborhoods’ based on the cell types that surround each cell in the sample. The presence and location of these neighborhoods can be compared across slides or within distinct regions within a tissue. Within a newly generated cycIHC dataset consisting of 6 glioblastoma tissue sections processed through 8 cycles of chromogenic IHC staining, CASSATT successfully identified populations detected in parallel flow cytometry analyses and revealed specific associations between tumor and immune populations. Additional successful benchmarking was completed on a published tissue microarray dataset consisting of 107 cores processed through 18 cycles of staining and imaging.

Design and implementation of smart power firefighting IoT based on massive heterogeneous terminals

This paper is mainly aimed at a large number of old, unintelligent power system terminals, a set of intelligent IoT framework solutions with overall coordination, linkage, and perception have been researched and designed to solve the real-time monitoring of various terminal abnormalities and faults in the unattended situation. The specific methods here are as follows. First, a status monitor to the back end of the old equipment is added for grasping the operational health index of each terminal in real time. Secondly, the thermal imaging module, the fire water system module, and the fire alarm module are introduced to build a power fire monitoring network that can cover the entire area. Then, on the basis of setting thresholds for each monitoring module, advanced information network processing technology is used to realise fault warning for each monitoring object in the area. Finally, a statistical analysis module is embedded in the background to perform real-time statistics on various fire protection malfunctions and monitor the completion rate of each unit's failure rectification.

Research on Diagnostic Information of Smart Medical Care Based on Big Data.

The medical field has gradually become intelligent, and information and the research of intelligent medical diagnosis information have received extensive attention in the medical field. In response to this situation, this paper proposes a Hadoop-based medical big data processing system. The system first realized the ETL module based on Sqoop and the transmission function of unstructured data and then realized the distributed storage management function based on HDFS. Finally, a MapReduce algorithm with variable key values is proposed in the data statistical analysis module. Through simulation experiments on the system modules and each algorithm, the results show that because the traditional nondistributed big data acquisition module transmits the same scale of data, it consumes more than 3200 s and the transmission time exceeds 3000 s. The time consumption of smart medical care under the 6G protocol is 150 s, the transmission time is 146 s, and the time is reduced to 1/10 of the original. The research of intelligent medical diagnosis information based on big data has good rationality and feasibility.

Design of Visualization System for Horizontal Transportation Operation of Container Terminal

Aiming at the problem of resource allocation and planning of container trucks in container terminals, the visualization system for horizontal transportation operation of container terminals is designed based on virtual reality technology. The system mainly includes task allocation module, statistical analysis module and visualization module. Based on the real-time communication interface, the synchronous operation of physical scene and virtual scene is realized, which is convenient for remote and real-time control of field operation; based on the principle of the shortest total operation time, the vehicle transfer task is allocated to maximize the resource utilization; with the FCFS (first come first service), priority level and other scheduling strategies, the vehicle path planning is realized to avoid accidents such as collision; through statistics and analysis of data, workers can get real-time information such as vehicle status and total working hours. The scale-down experiment is designed to simulate the container transfer operation of the terminal, which verifies the function of the system. The overall solution of horizontal transportation operation for the container terminal is provided, which can promote the intelligent construction of the terminal.

Development of the Energy Method and Study of Algorithms for Predicting the Takeoff Trajectory of Aircraft

The article is devoted to the development and research of the method of predicting the events on the trajectory of takeoff, climb and overcome highrise obstacles on the course. The prediction method is based on the energy approach to flight control, created by us in previous works. The mathematical formulation of the method is the energy balance equation describing the mutual influence of all acting forces in the aircraft-engine-environment" system. In this article, the equation is extended to ground modes of movement along the runway. For this, a term is added to the equation that takes into account the action of braking forces from the chassis. The balance equation allows us to directly obtain an algorithm for calculating the length of the forward trajectory required for the accumulation of the required amount of terminal energy. Takeoff trajectory includes ground and air segments. Therefore, the possibility of overcoming the obstacle is fixed by the algorithm at the point of a possible decision to takeoff, taking into account the next air segment. This point is reached before the decision-making airspeed prescribed by the flight manual is reached. This advance warning of the possibility of takeoff improves situational awareness of the pilot, which reduces stress and reduces the risk of erroneous actions. A computer stand was developed for the research. Single launches and series of statistical tests are possible. Takeoff scenarios are generated in the stand operator window, as well as initial runway conditions, atmospheric disturbances, aircraft configuration, and obstacle coordinates are specified. The parameters of random errors in the takeoff weight and centering are assigned, as well as the noise of longitudinal overload measurements are set. A large volume of deterministic and statistical tests of algorithms for predicting events on the takeoff trajectory was performed at the stand. Using the statistical analysis module, the characteristics of the range prediction errors to the take-off decision point and the nose wheel separation point were calculated. Probability densities and histograms of error distribution over five characteristic zones of deviations from the mean are constructed. The confidence intervals for calculating the mathematical expectation are obtained. A prototype of an electronic indicator of the takeoff trajectory with marks of predictive characteristic coordinates has been developed.

Description of an integrated management system for invasive mosquitoes at entry-exit ports in Zhejiang, China

BackgroundAs mosquitoes are one of the most harmful creatures in the world, recent high-frequency interceptions of invasive mosquito species have emphasized the need to enhance the biological security of the Zhejiang Province in China. As such, an integrated management system should be implemented to monitor the vectors of mosquito-borne diseases during data digitization and the processing of permanent E-forms and provide an online one-stop identification service.MethodsThis system is a semi-open network built on the latest Microsoft.NET Framework, Active Server Page.NET (ASP.NET) and Internet Information Services (IIS) for the Windows 2000 service as a basic infrastructure platform. This creates a physical separation between the data input as the back-page intranet and the online automated Lucid identification as the front-page internet through the digital interchange platform and security firewall.ResultsThis system mainly comprises three core modules: automated statistical analysis of operational data, online vector identification and digital specimen storage management, in addition to accessory modules. The joint analysis of invasive and native data collected between 2011 and 2017 at 14 surveillance points in the Zhejiang Province, excluding Ningbo Port, provided insights into the geographical differences in species abundance and the dynamic nature of seasonal interception within the statistical analysis module. Most importantly, multi-access keys to mosquitoes based on Lucid software were loaded in the module for vector identification. Subscribers can utilize this procedure for the online identification of 2 subfamilies, 10 genera and 33 mosquitoes by selecting any typical morphological feature in the classification system that matches the current images at hand.ConclusionsOur report suggests that this system can enhance the ability to master the basic information on invasive mosquitoes and satisfy the increasing requirements for public health safety in the integrated management of vector-borne diseases.

"The Cell" and Learning Analytics: Users Performance Analysis in the Module "Chemical Composition of the Cell and Biological Membranes"

INTRODUCTION: Learning Analytics tools aim to analyze data that allows the understanding of the learning process; its association with Massive Open Online Courses (MOOC) brings an opportunity for research into learning effectiveness, once MOOCs users produces digital footprints that can be used to understand their relationship with the content and environment. OBJECTIVES: To analyze the performance of users of "The Cell" in the module "Cell Chemical Composition and Biological Membranes" aiming to identify the major points that may have influenced their performance. MATERIALS AND METHODS: "Chemical Composition of the Cell and Biological Membranes" is a module of the MOOC "The Cell", a course designed into a 3D cell virtual model developed by the Laboratory of Educational Technologies of the Unicamp. The module is composed of textual content, challenge, training game, and assessment. "The Cell" has an embedded Statistical Analysis Module (SAM), an LA tool that collects data and has analysis tools focused on the student’s performance and learning process. RESULTS AND DISCUSSION: Between November of 2015 and November of 2018, SAM has registered 2858 interactions involving 1114 users in the module. The average time to perform the training game was 3.45 minutes, and there was a significant difference in the scores average comparing users who did the activity below and above the average time: 54.10 and 70.44 points, respectively. A similar result was noticed for the assessment session, users who complete the task faster scored 48.83 on average, while users who take more time scored 52.83 on average. The average score in the assessment of users who did or did not took the training game was 51.20 and 36.75, respectively. CONCLUSION: The average time spent to carry out the activities is directly related to performance; the training game acts as a preparation for the assessment, reflected in the note.

STATISTICAL ANALYSIS OF DEMAND FOR TELECOMMUNICATIONS SERVICES FOR FORECASTING PURPOSES – STUDY OF THE IMPACT OF FACTORS NOT ARISING FROM THE CALENDAR

The aim of this study is to identify the impact of factors (not arising from the calendar) on the demand for connection services offered by a telecommunications operator. The theoretical part of the research presents the importance of the Prediction System (PS) as a kind of Decision Support System in the operational management of the telecommunications operator. Theoretical aspects of PS structure have been included. Special attention has been paid to the statistical analysis module (as the PS subsystem), which was implemented in the adopted (researched) scope in the empirical part of the research. The empirical part presents the results of statistical analyses of demand for telecommunications services in the scope enabling identification of the impact of factors not arising from the calendar (i.e. the impact of category of connection and type of subscribers) on the level and distribution of such demand. The presented research results provide premises for the construction of forecasting tools, carrying out the forecasting procedure and monitoring the forecasts, i.e. they provide the necessary premises for the implementation of subsequent components of the PS.

A GIS-based evaluation method of underground space resources for urban spatial planning: Part 2 application

Urban underground space (UUS) has been playing an important role in the urban development in recent years. The evaluation for its potential becomes essential for urban spatial planning. Previous research emphasized the fundamental data, while this paper not only emphasized the data provided by related departments, but also took into consideration the gap and relation between UUS and urban spatial planning. To provide theoretical support for urban spatial planning, this paper studied a method for evaluating UUS. In this method, an index system for UUS resource evaluation was put forward and its analytical process was based on the Geographic Information System (GIS) and some mathematical tools, such as the analytic hierarchy process (AHP), the most unfavorable grading method (MUGM) and the exclusive method (EM). Then this method was applied to UUS Master Plans and Detailed Regulatory Planning in Chinese cities, and proved to be relatively practicable. The research outcomes are presented in the form of two papers, each with a different focus. Part 1 aims to introduce the evaluation methodology, including construction suitability evaluation & potential value evaluation & volume estimation. Part 2 reports on applications of the method to Chinese cities of Tongren and Changzhou.Part 2 demonstrated the UUS resource evaluation methodology for Tongren city and Changzhou city in China. In Tongren, the UUS construction suitability and resource’s comprehensive quality (RCQ) evaluation was implemented on an urban scale. Firstly, factors influencing the potential for UUS, including the area’s landforms, engineering geology, hydrogeology, site stability, existing subsurface construction conditions, urban location, and land use were collected and analyzed based on GIS. Furthermore, a combination of AHP, MUGM and EM techniques were used in the analysis. Then the UUS construction suitability and RCQ distribution were got. The UUS layout structure was finally obtained based on RCQ distribution figure. Meanwhile, this case study shows that the area used for UUS accounts for only 2% of the effective utilization area of the whole city based on the volume estimation model. While for Changzhou, existing construction evaluation at the parcel scale was implemented for one downtown area. A “four steps” method was proposed to calculate the influence depth of building foundations based on the geographical statistical analysis module of GIS with an interpolation method. Flexible application of the method, with the addition of local project experience, can make the planners definitely determine which part of the area can be exploited. A flow chart of existing construction evaluation is finally presented.

SynLethDB: synthetic lethality database toward discovery of selective and sensitive anticancer drug targets

Synthetic lethality (SL) is a type of genetic interaction between two genes such that simultaneous perturbations of the two genes result in cell death or a dramatic decrease of cell viability, while a perturbation of either gene alone is not lethal. SL reflects the biologically endogenous difference between cancer cells and normal cells, and thus the inhibition of SL partners of genes with cancer-specific mutations could selectively kill cancer cells but spare normal cells. Therefore, SL is emerging as a promising anticancer strategy that could potentially overcome the drawbacks of traditional chemotherapies by reducing severe side effects. Researchers have developed experimental technologies and computational prediction methods to identify SL gene pairs on human and a few model species. However, there has not been a comprehensive database dedicated to collecting SL pairs and related knowledge. In this paper, we propose a comprehensive database, SynLethDB (http://histone.sce.ntu.edu.sg/SynLethDB/), which contains SL pairs collected from biochemical assays, other related databases, computational predictions and text mining results on human and four model species, i.e. mouse, fruit fly, worm and yeast. For each SL pair, a confidence score was calculated by integrating individual scores derived from different evidence sources. We also developed a statistical analysis module to estimate the druggability and sensitivity of cancer cells upon drug treatments targeting human SL partners, based on large-scale genomic data, gene expression profiles and drug sensitivity profiles on more than 1000 cancer cell lines. To help users access and mine the wealth of the data, we developed other practical functionalities, such as search and filtering, orthology search, gene set enrichment analysis. Furthermore, a user-friendly web interface has been implemented to facilitate data analysis and interpretation. With the integrated data sets and analytics functionalities, SynLethDB would be a useful resource for biomedical research community and pharmaceutical industry.

Research and Application on Reports Function of Protection Equipment Management Information System

The main task of the protection equipment management information system is statistical analysis, which requires presenting the analytical results in the form of reports. Therefore, the statistical analysis module of the system contains the reports of Evaluation Code with complex business logic and stable structure, as well as common analysis reports with simple business logic and flexible structure. As the growth of the business complexity and the requirements for diversification, existing reporting mode cannot adapt to the system. The reports component using B/S architecture, which adopts the independent engine mechanism, has become the developing trend of statistical reports.

INMEX—a web-based tool for integrative meta-analysis of expression data

The widespread applications of various ‘omics’ technologies in biomedical research together with the emergence of public data repositories have resulted in a plethora of data sets for almost any given physiological state or disease condition. Properly combining or integrating these data sets with similar basic hypotheses can help reduce study bias, increase statistical power and improve overall biological understanding. However, the difficulties in data management and the complexities of analytical approaches have significantly limited data integration to enable meta-analysis. Here, we introduce integrative meta-analysis of expression data (INMEX), a user-friendly web-based tool designed to support meta-analysis of multiple gene-expression data sets, as well as to enable integration of data sets from gene expression and metabolomics experiments. INMEX contains three functional modules. The data preparation module supports flexible data processing, annotation and visualization of individual data sets. The statistical analysis module allows researchers to combine multiple data sets based on P-values, effect sizes, rank orders and other features. The significant genes can be examined in functional analysis module for enriched Gene Ontology terms or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, or expression profile visualization. INMEX has built-in support for common gene/metabolite identifiers (IDs), as well as 45 popular microarray platforms for human, mouse and rat. Complex operations are performed through a user-friendly web interface in a step-by-step manner. INMEX is freely available at http://www.inmex.ca.

MALINA: a web service for visual analytics of human gut microbiota whole-genome metagenomic reads

MALINA is a web service for bioinformatic analysis of whole-genome metagenomic data obtained from human gut microbiota sequencing. As input data, it accepts metagenomic reads of various sequencing technologies, including long reads (such as Sanger and 454 sequencing) and next-generation (including SOLiD and Illumina). It is the first metagenomic web service that is capable of processing SOLiD color-space reads, to authors’ knowledge. The web service allows phylogenetic and functional profiling of metagenomic samples using coverage depth resulting from the alignment of the reads to the catalogue of reference sequences which are built into the pipeline and contain prevalent microbial genomes and genes of human gut microbiota. The obtained metagenomic composition vectors are processed by the statistical analysis and visualization module containing methods for clustering, dimension reduction and group comparison. Additionally, the MALINA database includes vectors of bacterial and functional composition for human gut microbiota samples from a large number of existing studies allowing their comparative analysis together with user samples, namely datasets from Russian Metagenome project, MetaHIT and Human Microbiome Project (downloaded from http://hmpdacc.org). MALINA is made freely available on the web at http://malina.metagenome.ru. The website is implemented in JavaScript (using Ext JS), Microsoft .NET Framework, MS SQL, Python, with all major browsers supported.

자동차 환경내의 음성인식 자동 평가 플랫폼 연구

주행 중 차량내의 음성인터페이스 에서 음성인식기의 성능은 가장 중요한 부분이다. 본 논문은 차량내 음성인식기의 성능 평가를 자동화하기 위한 플랫폼의 개발에 대한 것이다. 개발된 플랫폼은 주 프로그램, 중계 프로그램 데이터베이스 관리, 통계산출 모듈로 구성된다. 성능 평가에 있어 실제 차량의 주행 조건을 고려한 시뮬레이션 환경이 구축되었고, 미리 녹음된 주행 노이즈와 발화자의 목소리를 마이크를 통해 입력하여 실험하였다. 실험 결과 제안하는 플랫폼에서 얻어진 음성인식 결과의 유효성이 입증되었다. 제안한 플랫폼으로 사용자는 음성인식의 자동화와 인식결과의 효율적인 관리 및 통계산출을 함으로서 차량 음성인식기의 평가를 효과적으로 진행할 수 있다. The performance of the speech recognition engine is one of the most critical elements of the in-vehicle speech recognition interface. The objective of this paper is to develop an automated platform for running performance tests on the in-vehicle speech recognition engine. The developed platform comprise of main program, agent program, database management module, and statistical analysis module. A simulation environment for performance tests which mimics the real driving situations was constructed, and it was tested by applying pre-recorded driving noises and a speaker's voice as inputs. As a result, the validity of the results from the speech recognition tests was proved. The users will be able to perform the performance tests for the in-vehicle speech recognition engine effectively through the proposed platform.

Increase students’ engagement in the classroom

In this study of we investigated student engagements of level 4 statistical analysis module with a specific interest of how to raise the motivation. We used observation to get into root of problems. We implemented some strategies to increase students' involvement in the class room. We are pleased with the results have achieved. After eight weeks of study we noticed that our strategies helped the students to involve more in the class room and they started enjoying learning statistics. We as teachers should consider action as a continuous process in educational context. We could expand our knowledge using observation. We started our class with a warm up task for about 20 minutes. It helped students to relax and they could start focusing on what they are doing. It also creates a friendly environment. After that we gave them a group activity, using games which put groups against each other to help students' to learn.

P-315 - Anxiety levels and awareness of God in adolescents

Spirituality and mental health have always been in a very dynamic relationship. One can wonder if spirituality should be taken out of psychiatry or if psychiatry lost its faith. The goal of this research is to analyze how anxiety levels are influenced by religious beliefs and practices in children and adolescents. 72 respondents participated in our study. They were pupils in the eighth grade at Scoala Generala Horea, Cluj-Napoca, Romania. The exclusion criteria was any psychiatric disorder diagnosed prior to the research. We used the questionnaire for anxiety, S.T.A.I. - State Trait Anxiety Inventory (Charles D. Spielberger Ph.D., 1970). The questionnaires about religious beliefs, behaviors and personal motivation: SAI -Spiritual Assessment Inventory (Todd W. Hall, Ph.D&Keith J. Edwards, Ph.D, 1996) and two questions from DUREL - Duke University Religion Index (Koenig HG, Meador K, Parkerson G., 1997). These questionnaires are adapted for a monotheist religion. To analyze the results, we used SPSS, a Business Intelligence software which includes statistical analysis modules, version 17. The results identified a valid statistical correlation between anxiety levels and the degree of awareness of God in religious practices and beliefs. (Pearson correlation −0.227, p = 0.05). Depending on the results from SAI questionnaire concerning the level of awareness, we formed 2 groups and we studied the anxiety levels. The analysis of these 2 groups sustained the prior association. The anxiety levels are lower in children with high degree of spiritual awareness and religious practices and beliefs.

Inhibition of Transcription Factor Specificity Protein 1 Alters the Gene Expression Profile of Keratinocytes Leading to Upregulation of Kallikrein-Related Peptidases and Thymic Stromal Lymphopoietin

Transcription factor specificity protein 1 (Sp1) is involved in diverse cellular functions. We recently found that Sp1 was significantly decreased in skin biopsies from patients with atopic dermatitis (AD) and had an even greater reduction in AD patients with a history of eczema herpeticum. In the current study, we sought to better understand the role of Sp1 in skin biological processes by using a small interfering RNA (siRNA) technique to knock down Sp1 gene expression in normal human keratinocytes (NHK) and investigated the genome-wide gene expression profiling of Sp1- silenced NHK. The gene arrays revealed that 53 genes had more than three-fold changes in expression in Sp1-silenced NHK as compared to scrambled siRNA silenced cells. Strikingly, six kallikrein-related peptidase genes, KLK5, KLK6, KLK7, KLK8, KLK10, and KLK12 were up-regulated in NHK following Sp1 silencing. Functionally, protease activity was significantly enhanced in Sp1-silenced keratinocytes as compared to scrambled siRNA silenced keratinocytes. Moreover, thymic stromal lymphopoietin (TSLP), an epithelial derived TH2 promoting cytokine, was induced in Sp1-silenced keratinocytes due to elevated kallikrein activity. These results indicate that Sp1 expression deficiency leads to abnormally increased kallikrein protease activity in keratinocytes and may contribute to TH2 immune responses in the skin by inducing TSLP.

Adding automated data analysis and biological evaluation to affyanalysisQC

AbstractAlmost every cell in the body contains a full set of chromosomes and identical genes. However, only a fraction of these genes are turned on, at any given time and it is this subset of genes that are expressed, which confers unique properties to each cell type. Gene expression is the term used to describe the transcription of the information contained within the DNA into messenger RNA (mRNA) molecules that are then translated into proteins which perform most of the critical functions of cells.Gene expression is a highly complex and tightly regulated process that allows a cell to respond dynamically both to environmental stimuli and to its own changing needs. This mechanism acts as both an on/off switch to control which genes are expressed in a cell as well as a volume control that increases or decreases the level of expression of particular genes as necessary. The proper and harmonious expression of a large number of genes is a critical component of normal growth and development and the maintenance of proper health. Disruptions or changes in gene expression are responsible for many diseases. Scientists study the kinds and amounts of mRNA produced by a cell to learn which genes are expressed, which in turn provides insights into how the cell responds to its changing needs.Biomedical research evolves and advances not only through the compilation of knowledge but also through the development of new technologies. Using traditional methods to assay gene expression, researchers were able to survey a relatively small number of genes at a time. The emergence of new tools enables researchers to address previously intractable problems and to uncover novel potential targets for therapies. Microarrays allow scientists to analyze expression of many genes in a single experiment quickly and efficiently.Microarray technologies are currently used to try to understand fundamental aspects of growth and development as well as to explore the underlying genetic causes of many human diseases. DNA Microarrays are small, solid supports onto which the sequences from thousands of different genes are immobilized, or attached, at fixed locations. The supports themselves are usually glass microscope slides, silicon chips or nylon membranes. The DNA is printed, spotted, or actually synthesized directly onto the support. There are three basic types of samples that can be used to construct DNA microarrays, two are genomic and the other is transcriptomic, that is, it measures mRNA levels.In order to use the huge amount of data obtained from these platforms microarray data must be efficiently analyzed. Affymetrix microarrays of different technology versions are very often used in transcriptomics analysis. Quality control and normalization approaches do exist, especially as packages in Bioconductor/R. However they are not always easy to access as they run through command lines and it is often not clear what the meaning of the specific settings and results are.To tackle this, the BiGCaT department of bioinformatics at Maastricht University, proposed an automated, well-documented and user-friendly pipeline the affyanalysisQC workflow which is called by the www.arrayanalysis.org server. The existing workflow allows for the quality control (QC) and preprocessing (normalisation) of Affymetrix microarray gene expression data sets. The code called by the webform can alternatively be run locally in R by setting few parameters in an initialization file. However the functionality offered by the affyanalysisQC needs to be extended for statistical analysis of normalized data and visualizing genes of interest on pathways for biological evaluation of the data. The presentation illustrates the extension of the pipeline by adding automated statistical analysis and biological evaluation modules to affyanalysisQC.The affyanalysisQC workflow's functionality is to be extended by this project. The methods developed in the project presented in this presentation do not have to be developed from scratch. The statistical analysis module uses the functionality of the R/Bioconductor package LIMMA and the visualization of genes on pathways uses the basic functions provided by www.pathvisio.org extended with a pathvisioRPC package developed by using XMLRPC to allow automated calls from the www.arrayanalysis.org server for direct pathway visualization of the genes analyzed.