Quantized correlation coefficient for measuring reproducibility of ChIP-chip data

Background  

Chromatin immunoprecipitation followed by microarray hybridization (ChIP-chip) is used to study protein-DNA interactions and histone modifications on a genome-scale. To ensure data quality, these experiments are usually performed in replicates, and a correlation coefficient between replicates is used often to assess reproducibility. However, the correlation coefficient can be misleading because it is affected not only by the reproducibility of the signal but also by the amount of binding signal present in the data.     

Quality determination and the repair of poor quality spots in array experiments

Background  

A common feature of microarray experiments is the occurence of missing gene expression data. These missing values occur for a variety of reasons, in particular, because of the filtering of poor quality spots and the removal of undefined values when a logarithmic transformation is applied to negative background-corrected intensities. The efficiency and power of an analysis performed can be substantially reduced by having an incomplete matrix of gene intensities. Additionally, most statistical methods require a complete intensity matrix. Furthermore, biases may be introduced into analyses through missing information on some genes. Thus methods for appropriately replacing (imputing) missing data and/or weighting poor quality spots are required.     

The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays

Background  

Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, production and manipulations are limiting factors, affecting data quality. The use of customized DNA microarrays improves overall data quality in many situations, however, only if for these specifically designed microarrays analysis tools are available.     

A new wireless system for decentralised measurement of physiological parameters from shake flasks

Background  

Shake flasks are widely used because of their low price and simple handling. Many researcher are, however, not aware of the physiological consequences of oxygen limitation and substrate overflow metabolism that occur in shake flasks. Availability of a wireless measuring system brings the possibilities for quality control and design of cultivation conditions.     

Veterinary decision making in relation to metritis - a qualitative approach to understand the background for variation and bias in veterinary medical records

Background  

Results of analyses based on veterinary records of animal disease may be prone to variation and bias, because data collection for these registers relies on different observers in different settings as well as different treatment criteria. Understanding the human influence on data collection and the decisions related to this process may help veterinary and agricultural scientists motivate observers (veterinarians and farmers) to work more systematically, which may improve data quality. This study investigates qualitative relations between two types of records: 1) 'diagnostic data' as recordings of metritis scores and 2) 'intervention data' as recordings of medical treatment for metritis and the potential influence on quality of the data.     

Characterization and comparative analysis of HMW glutenin 1Ay alleles with differential expressions

Background  

High-molecular-weight glutenin subunits (HMW-GSs) have been considered as most important seed storage proteins for wheat flour quality. 1Ay subunits are of great interest because they are always silent in common wheat. The presence of expressed 1Ay subunits in diploid and tetraploid wheat genotypes makes it possible to investigate molecular information of active 1Ay genes.     

SolexaQA: At-a-glance quality assessment of Illumina second-generation sequencing data

Background  

Illumina's second-generation sequencing platform is playing an increasingly prominent role in modern DNA and RNA sequencing efforts. However, rapid, simple, standardized and independent measures of run quality are currently lacking, as are tools to process sequences for use in downstream applications based on read-level quality data.     

An analysis of extensible modelling for functional genomics data

Background  

Several data formats have been developed for large scale biological experiments, using a variety of methodologies. Most data formats contain a mechanism for allowing extensions to encode unanticipated data types. Extensions to data formats are important because the experimental methodologies tend to be fairly diverse and rapidly evolving, which hinders the creation of formats that will be stable over time.     

Empirical array quality weights in the analysis of microarray data

Background  

Assessment of array quality is an essential step in the analysis of data from microarray experiments. Once detected, less reliable arrays are typically excluded or "filtered" from further analysis to avoid misleading results.     

<Emphasis Type="Italic">ClustalXeed</Emphasis>: a GUI-based grid computation version for high performance and terabyte size multiple sequence alignment

Background  

There is an increasing demand to assemble and align large-scale biological sequence data sets. The commonly used multiple sequence alignment programs are still limited in their ability to handle very large amounts of sequences because the system lacks a scalable high-performance computing (HPC) environment with a greatly extended data storage capacity.     

Missing value imputation for microarray gene expression data using histone acetylation information

Background  

It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile analysis in bioinformatics. Although several methods have been suggested, their performances are not satisfactory for datasets with high missing percentages.     

How high is the level of technical noise in microarray data?

Background  

Microarray gene expression data are commonly perceived as being extremely noisy because of many imperfections inherent in the current technology. A recent study conducted by the MicroArray Quality Control (MAQC) Consortium and published in Nature Biotechnology provides a unique opportunity to probe into the true level of technical noise in such data.     

Commentary on issues in data quality analysis in life cycle assessment

Purpose  

For compliance with the ISO standard 14044, comparative life cycle assessments are required to address data quality for time-related coverage, geographic coverage, technology coverage, precision, completeness, representativeness, consistency, reproducibility, sources of the data and uncertainty of the information. As the community of practitioners and data developers grows, the purpose of this commentary is to initiate discussion of current issues and opportunities for improvement in data quality analysis.     

Portraits of breast cancer progression

Background  

Clustering analysis of microarray data is often criticized for giving ambiguous results because of sensitivity to data perturbation or clustering techniques used. In this paper, we describe a new method based on principal component analysis and ensemble consensus clustering that avoids these problems.     

Analysis of expressed sequence tags from a single wheat cultivar facilitates interpretation of tandem mass spectrometry data and discrimination of gamma gliadin proteins that may play different functional roles in flour

Background  

The gamma gliadins are a complex group of proteins that together with other gluten proteins determine the functional properties of wheat flour. The proteins have unusually high levels of glutamine and proline and contain large regions of repetitive sequences. While most gamma gliadins are monomeric proteins containing eight conserved cysteine residues, some contain an additional cysteine residue that enables them to be linked with other gluten proteins into large polymers that are critical for flour quality. The ability to differentiate among the gamma gliadins is important for studies of wheat flour quality because proteins with similar sequences can have different effects on functional properties.     

Discarding duplicate ditags in LongSAGE analysis may introduce significant error

Background  

During gene expression analysis by Serial Analysis of Gene Expression (SAGE), duplicate ditags are routinely removed from the data analysis, because they are suspected to stem from artifacts during SAGE library construction. As a consequence, naturally occurring duplicate ditags are also removed from the analysis leading to an error of measurement.     

Using jackknife to assess the quality of gene order phylogenies

Background  

In recent years, gene order data has attracted increasing attention from both biologists and computer scientists as a new type of data for phylogenetic analysis. If gene orders are viewed as one character with a large number of states, traditional bootstrap procedures cannot be applied. Researchers began to use a jackknife resampling method to assess the quality of gene order phylogenies.     

Comparison of normalization methods for CodeLink Bioarray data

Background  

The quality of microarray data can seriously affect the accuracy of downstream analyses. In order to reduce variability and enhance signal reproducibility in these data, many normalization methods have been proposed and evaluated, most of which are for data obtained from cDNA microarrays and Affymetrix GeneChips. CodeLink Bioarrays are a newly emerged, single-color oligonucleotide microarray platform. To date, there are no reported studies that evaluate normalization methods for CodeLink Bioarrays.     

Merged consensus clustering to assess and improve class discovery with microarray data

Background  

One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a large number of methods available to perform clustering, but it is often unclear which method is best suited to the data and how to quantify the quality of the classifications produced.     

Array-A-Lizer: A serial DNA microarray quality analyzer

Background  

The proliferate nature of DNA microarray results have made it necessary to implement a uniform and quick quality control of experimental results to ensure the consistency of data across multiple experiments prior to actual data analysis.