Expression Analysis
Identify, visualize, and classify differentially expressed genes and
expression profiles
Functions
mattest | Perform two-sample t-test to evaluate differential expression of genes from two experimental conditions or phenotypes |
mafdr | Estimate positive false discovery rate for multiple hypothesis testing |
mavolcanoplot | Create significance versus gene expression ratio (fold change) scatter plot of microarray data |
mairplot | Create intensity versus ratio scatter plot of microarray data |
maboxplot | Create box plot for microarray data |
maloglog | Create loglog plot of microarray data |
mapcaplot | Create Principal Component Analysis (PCA) plot of microarray data |
nbintest | Unpaired hypothesis test for count data with small sample sizes |
redbluecmap | Create red and blue colormap |
redgreencmap | Create red and green colormap |
probesetplot | Plot Affymetrix probe set intensity values |
metafeatures | Attractor metagene algorithm for feature engineering using mutual information-based learning |
rankfeatures | Rank key features by class separability criteria |
randfeatures | Generate randomized subset of features |
knnimpute | Impute missing data using nearest-neighbor method |
crossvalind | Generate indices for training and test sets |
classperf | Evaluate classifier performance |
Classes
DataMatrix | Create DataMatrix object |
DataMatrix object | Data structure encapsulating data and metadata from microarray experiment so that it can be indexed by gene or probe identifiers and by sample identifiers |
bioma.ExpressionSet | Contain data from microarray gene expression experiment |
bioma.data.ExptData | Contain data values from microarray experiment |
bioma.data.MetaData | Contain metadata from microarray experiment |
bioma.data.MIAME | Contain experiment information from microarray gene expression experiment |
NegativeBinomialTest | Unpaired hypothesis test result |
HeatMap | Object containing matrix and heatmap display properties |
clustergram | Object containing hierarchical clustering analysis data |
Topics
- Managing Gene Expression Data in Objects
Overview of objects for Microarray Gene Expression Data
- Representing Expression Data Values in DataMatrix Objects
Construct DataMatrix objects, get and set properties, and access data.
- Representing Expression Data Values in ExptData Objects
Construct ExptData objects, use properties and methods, and access data.
- Representing Sample and Feature Metadata in MetaData Objects
Construct MetaData objects, use properties and methods, and access data.
- Representing Experiment Information in a MIAME Object
Construct MIAME objects, use properties and methods, and access data.
- Representing All Data in an ExpressionSet Object
Construct ExpressionSet objects, use properties and methods, and access data.
- Microarray Data Analysis Tools
The MATLAB® environment is widely used for microarray data analysis, including reading, filtering, normalizing, and visualizing microarray data.
- Statistical Learning and Visualization
You can classify and identify features in data sets, set up cross-validation experiments, and compare different classification methods.