|
LC Sciences provides access to Gene Expression Analysis Service through our partnership with SeqWright DNA Technology Services.
SeqWright is an
Affymetrix®
Authorized Service Provider with over 30 years of combined experience involving microarray technologies used in both industry and diagnostic environments. SeqWright's
Affymetrix® service is GLP-compliant and CLIA certified for handling patient samples.
| Comprehensive Service Available |
√ |
| Microarray Platform |
Affymetrix Genechip® Technology |
| Starting Sample Material |
Total RNA, mRNA, Blood,
Cell Pellet, Tissue, FFPE |
| Sample QC |
Agilent 2100 Bioanalyzer RNA LabChip
Nanodrop ND-1000 |
| 2-cycle Target labeling for low quantities of RNA available |
√ |
| Species Covered |
All species for which Affymetrix GeneChip® brand arrays exists |
| Full Data Analysis Included |
√ |
| Data Delivery Time |
1 week |
| GLP Compliant |
√ |
Standard Analyses of Expression Microarray Data
Computation of a global normalized expression metric using Robust Multiarray Average (RMA) of the hybridization intensity data from all chips in the experimental set
(Probe annotations will be added at this step.)
QC Analysis:
- Histograms for PM intensity data
- Pattern of 5’-3’ probe RNA degradation
Experiments with 2 conditions:
- Analysis of the pattern of expressed and non-expressed transcripts with screening of genes for later analyses
- Parametric (t-test) or nonparametric (Mann-Whitney U-test) for significant differences in patterns of expression between groups
- Within-gene permutation testing for empirical significance with and without randomization
Experiments with 3 or more conditions
- Analysis of the pattern of expressed and non-expressed transcripts with screening of genes for later analyses
- Parametric F-test (ANOVA) or non-parametric (Kruskal-Wallis) for significant differences in patterns of expression between groups
- Within-gene permutation testing for empirical significance with and without randomization
Computation of Positive False Discovery Rate (pFDR) statistics using Storey q-value
Exploratory Data Analysis
- K-means cluster analysis using agglomeration and distance measures to search for patterns of sample and/or transcript clustering - production of corresponding heatmap
- Other exploratory data methods available – Principal Components, Factor Analysis, Linear Discriminant Analysis,
Canonical Discriminant Analysis
|
