Quality control and conduct of genome-wide association meta-analyses.

Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC at the study file level, the meta-level across studies and the meta-analysis output level. Real-world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for the use of a powerful and flexible software package called EasyQC. Precise timings will be greatly influenced by consortium size. For consortia of comparable size to the GIANT Consortium, this protocol takes a minimum of about 10 months to complete.

IQRray, a new method for Affymetrix microarray quality control, and the homologous organ conservation score, a new benchmark method for quality control metrics.

MOTIVATION: Microarray results accumulated in public repositories are widely reused in meta-analytical studies and secondary databases. The quality of the data obtained with this technology varies from experiment to experiment, and an efficient method for quality assessment is necessary to ensure their reliability. RESULTS: The lack of a good benchmark has hampered evaluation of existing methods for quality control. In this study, we propose a new independent quality metric that is based on evolutionary conservation of expression profiles. We show, using 11 large organ-specific datasets, that IQRray, a new quality metrics developed by us, exhibits the highest correlation with this reference metric, among 14 metrics tested. IQRray outperforms other methods in identification of poor quality arrays in datasets composed of arrays from many independent experiments. In contrast, the performance of methods designed for detecting outliers in a single experiment like Normalized Unscaled Standard Error and Relative Log Expression was low because of the inability of these methods to detect datasets containing only low-quality arrays and because the scores cannot be directly compared between experiments. AVAILABILITY AND IMPLEMENTATION: The R implementation of IQRray is available at: ftp://lausanne.isb-sib.ch/pub/databases/Bgee/general/IQRray.R. CONTACT: Marta.Rosikiewicz@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Contrôle de la qualité des soins: aspects épidémiologiques. [Quality control of health care: epidemiological aspects].

Quality control in health care should be performed by health professionals. To do so they must define indicators, set up studies aimed at measuring and analyzing quality of care, and implement quality assurance programs in health care systems. The elements of a quality improvement program of this kind are described, with special emphasis on the contribution of epidemiology in this field.

Formulation and Implementation of Air Quality Control Pogrammes : Patterns of Interest Consideration

This article investigates some central aspects of the relationships between programme structure and implementation of sulphur dioxide air quality control policies. Previous implementation research, primarily adopting American approaches, has neglected the connections between the processes of programme formulation and implementation. 'Programme', as the key variable in implementation studies, has been defined too narrowly. On the basis of theoretical and conceptual reflections and provisional empirical results from studies in France, Italy, England, and the Federal Republic of Germany, the authors demonstrate that an integral process analysis using a more extended programme concept is necessary if patterns of interest recognition in policies are to be discovered. Otherwise, the still important question of critical social science cannot be answered, namely, what is the impact of special interests upon implementation processes.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Hematopoietic stem cell transplantation in Switzerland: a comprehensive quality control report on centre effect.

Interest groups advocate centre-specific outcome data as a useful tool for patients in choosing a hospital for their treatment and for decision-making by politicians and the insurance industry. Haematopoietic stem cell transplantation (HSCT) requires significant infrastructure and represents a cost-intensive procedure. It therefore qualifies as a prime target for such a policy. We made use of the comprehensive database of the Swiss Blood Stem Cells Transplant Group (SBST) to evaluate potential use of mortality rates. Nine institutions reported a total of 4717 HSCT - 1427 allogeneic (30.3%), 3290 autologous (69.7%) - in 3808 patients between the years 1997 and 2008. Data were analysed for survival- and transplantation-related mortality (TRM) at day 100 and at 5 years. The data showed marked and significant differences between centres in unadjusted analyses. These differences were absent or marginal when the results were adjusted for disease, year of transplant and the EBMT risk score (a score incorporating patient age, disease stage, time interval between diagnosis and transplantation, and, for allogeneic transplants, donor type and donor-recipient gender combination) in a multivariable analysis. These data indicate comparable quality among centres in Switzerland. They show that comparison of crude centre-specific outcome data without adjustment for the patient mix may be misleading. Mandatory data collection and systematic review of all cases within a comprehensive quality management system might, in contrast, serve as a model to ascertain the quality of other cost-intensive therapies in Switzerland.

Selectome update: quality control and computational improvements to a database of positive selection.

Selectome (http://selectome.unil.ch/) is a database of positive selection, based on a branch-site likelihood test. This model estimates the number of nonsynonymous substitutions (dN) and synonymous substitutions (dS) to evaluate the variation in selective pressure (dN/dS ratio) over branches and over sites. Since the original release of Selectome, we have benchmarked and implemented a thorough quality control procedure on multiple sequence alignments, aiming to provide minimum false-positive results. We have also improved the computational efficiency of the branch-site test implementation, allowing larger data sets and more frequent updates. Release 6 of Selectome includes all gene trees from Ensembl for Primates and Glires, as well as a large set of vertebrate gene trees. A total of 6810 gene trees have some evidence of positive selection. Finally, the web interface has been improved to be more responsive and to facilitate searches and browsing.

Current and future trens in the quality control of pharmaceuticals and biopharmaticals : impacts on Cost of Goods Sold (COGS)

[Summary] 2. Roles of quality control in the pharmaceutical and biopharmaceutical industries. - 2.1. Pharmaceutical industry. - 2.2. Biopharmaceutical industry. - 2.3. Policy and regulatory. - 2.3.1. The US Food and Drug Administration (FDA). - 2.3.2. The European Medicine Agency (EMEA). - 2.3.3. The Japanese Ministry of Work, Labor and Welfare (MHLW). - 2.3.4. The Swiss Agency for Therapeutic Products (Swissmedic). - 2.3.5. The International Conference on Harmonization (ICH). - - 3. Types of testing. - 3.1. Microbiological purity tests. - 3.2. Physiochemical tests. - 3.3. Critical to quality steps. - 3.3.1. API starting materials and excipients. - 3.3.2. Intermediates. - 3.3.3. APIs (drug substances) and final drug product. - 3.3.4. Primary and secondary packaging materials fro drug products. - - 4. Manufacturing cost and quality control. - 4.1.1. Pharmaceutical manufacturing cost breakdown. - 4.1.2. Biopharmaceutical manufacturing cost breakdown. - 4.2. Batch failure / rejection / rework / recalls. - - 5. Future trends in the quality control of pharmaceuticals and biopharmaceuticals. - 5.1. Rapid and real time testing. - 5.1.1. Physio-chemicals testing. - 5.1.2. Rapid microbiology methods

MSight: an image analysis software for liquid chromatography-mass spectrometry.

Images obtained from high-throughput mass spectrometry (MS) contain information that remains hidden when looking at a single spectrum at a time. Image processing of liquid chromatography-MS datasets can be extremely useful for quality control, experimental monitoring and knowledge extraction. The importance of imaging in differential analysis of proteomic experiments has already been established through two-dimensional gels and can now be foreseen with MS images. We present MSight, a new software designed to construct and manipulate MS images, as well as to facilitate their analysis and comparison.

Automatic quality assessment in structural brain magnetic resonance imaging

MRI has evolved into an important diagnostic technique in medical imaging. However, reliability of the derived diagnosis can be degraded by artifacts, which challenge both radiologists and automatic computer-aided diagnosis. This work proposes a fully-automatic method for measuring image quality of three-dimensional (3D) structural MRI. Quality measures are derived by analyzing the air background of magnitude images and are capable of detecting image degradation from several sources, including bulk motion, residual magnetization from incomplete spoiling, blurring, and ghosting. The method has been validated on 749 3D T(1)-weighted 1.5T and 3T head scans acquired at 36 Alzheimer's Disease Neuroimaging Initiative (ADNI) study sites operating with various software and hardware combinations. Results are compared against qualitative grades assigned by the ADNI quality control center (taken as the reference standard). The derived quality indices are independent of the MRI system used and agree with the reference standard quality ratings with high sensitivity and specificity (>85%). The proposed procedures for quality assessment could be of great value for both research and routine clinical imaging. It could greatly improve workflow through its ability to rule out the need for a repeat scan while the patient is still in the magnet bore.

EuroDia: a beta-cell gene expression resource.

Type 2 diabetes mellitus (T2DM) is a major disease affecting nearly 280 million people worldwide. Whilst the pathophysiological mechanisms leading to disease are poorly understood, dysfunction of the insulin-producing pancreatic beta-cells is key event for disease development. Monitoring the gene expression profiles of pancreatic beta-cells under several genetic or chemical perturbations has shed light on genes and pathways involved in T2DM. The EuroDia database has been established to build a unique collection of gene expression measurements performed on beta-cells of three organisms, namely human, mouse and rat. The Gene Expression Data Analysis Interface (GEDAI) has been developed to support this database. The quality of each dataset is assessed by a series of quality control procedures to detect putative hybridization outliers. The system integrates a web interface to several standard analysis functions from R/Bioconductor to identify differentially expressed genes and pathways. It also allows the combination of multiple experiments performed on different array platforms of the same technology. The design of this system enables each user to rapidly design a custom analysis pipeline and thus produce their own list of genes and pathways. Raw and normalized data can be downloaded for each experiment. The flexible engine of this database (GEDAI) is currently used to handle gene expression data from several laboratory-run projects dealing with different organisms and platforms. Database URL: http://eurodia.vital-it.ch.