Advanced Genomics Bioinformatics Services

Data Quality Control:

The challenge of making reproducible microarray data is to tackle it from various directions, otherwise data interpretation may be misleading. Variability is caused by experimental set up, labeling efficiency, data acquisition, data analysis, disguised actual differences in signal intensities, and cy3/cy5 channel intensities. Our team of statistics and bioinformatics is skilled in handling all these systematic and random variables. In addition to primary attention to minimize variabilities (i.e. biological and technical replicates, and data processing such as filtration, transformation and normalization), main emphasis is placed on data quality and advanced filtering techniques. Our team uses robust statistical approaches to measure quality of microarray data as well as identify quality control problems based on measures provided in the QC report. Multivariable analysis is used to compare quality across the arrays, rank them according to quality and remove any considered defect. They handle:

• All systematic and random variables
• Biological and technical replicates
• Data processing such as filtration, transformation and normalization
• Data quality control
• Advance filtering techniques to compare differentially expressed genes
• Identify quality control problems based on measures provided in the QC report