Gene Expression
Data Deliverables for Expression Assays
QC Results - This report contains the QC results collected for each sample during target preparation and hybridization, such as spectrophotometer readings and hybridization metrics.
Raw Data Files - Expression Analysis returns the primary, platform-specific data files and text files that can be incorporated into analysis software.
Data Summaries and Comparisons – This file assimilates expression data, such as signal intensities and detection calls for every sample in a common study, and includes substantial gene annotation information. We also provide basic comparisons between control and treated samples.
Custom Analysis Services • Expression Analysis is equipped to provide custom analysis services, including:
- Alternative Measures of Expression (e.g., PLIER and PLIER variants, RMA, GCRMA, PDNN, or dCHIP)
- Alternative Chip Normalization Techniques (e.g., quantile, invariant set, median scaling, z-scaling)
- Principal Components Analysis and related graphs to detect outliers and hidden factors in samples
- Hierarchical Clustering with Heat Maps
- ANOVA/Linear Model Analysis including repeated measures analysis
- Analysis of differential gene list related to potential enrichment of GO terms or pathways
- Biomarker prediction and validation
- Predictive signature model robustness and sensitivity analysis
- Advanced Statistical Graphics
Two-Group Comparison with Permutation Analysis for Differential Expression (PADE)
Expression Analysis provides a two-group comparison analysis to detect and estimate changes in expression between two experimental groups that are each represented by multiple specimens per group. The comparison incorporates a permutation analysis for differential expression (PADE™). This analysis helps to mitigate false positives, a very important consideration when analyzing whole genome chips where potentially tens of thousands of statistical tests are examined in parallel. Expression Analysis also provides a two-group comparison analysis for repeated measures designs (RM-PADE) to account for those experiments or clinical trials when the subjects are used as their own matched control.
Reduction of Invariant Probes (REDI)
Most Affymetrix GeneChips contain multiple oligonucleotide probes for interrogating the same transcript. Through an examination of thousands of hybridization experiments, Expression Analysis has established that certain Perfect Match probes fail to respond adequately to the amount of target transcript in a sample. Our research shows that roughly 30% of the PM probes are poorly performing, affecting 80% of the probe sets. Probe sets that contain these invariant probe sequences are compromised in their ability to discern variations in transcript levels, thereby reducing sensitivity and the magnitude of differential expression values. Expression Analysis developed REDI analysis to remove these invariant probes from data analysis, resulting in the detection of more differentially expressed transcripts. This method is available for the HG-U133 family, the Rat230 family, and the Mouse430 family of GeneChips.