Analysis tools for microarray data

Every tool is described in detail on its own help page. The help page is divided into four parts: General description, Parameters, Details on how the tool works, and Output where the results are described. The Parameters part contains the list of parameters, their possible values (1-100) and their default values [10].

1. Normalization
2. Quality control
3. Preprocessing
4. Statistics
5. Clustering
6. Annotation
7. Pathways
8. Promoter analysis
9. Copy number aberrations
10. Visualization
11. Utilities

Normalization
• Affymetrix
• Affymetrix exon arrays
• Affymetrix gene arrays
• Affymetrix SNP arrays
• Agilent 1-color
• Agilent 2-color
• Agilent miRNA
• cDNA
• Illumina
• Illumina with normexp background correction
• Illumina - lumi pipeline
• Illumina - methylumi pipeline
• Illumina SNP arrays
• Process prenormalized
• Process prenormalized affy
• Random effects
• ComBat - batch normalisation
• Normalize to chip average
• Normalize to gene average
• Normalize to specific samples
• Normalize to specific genes


Quality control
• Affymetrix basic
• Affymetrix - using RLE and NUSE
• Affymetrix exon/gene arrays - using RLE and NUSE
• Illumina
• Agilent 2-color
• Agilent 1-color
• cDNA


Preprocessing
• Filter by expression
• Filter by flags
• Filter by standard deviation
• Filter by interquartile range
• Filter by coefficient of variation
• Filter by column term
• Filter by column value
• Impute missing values
• Remove missing values
• Dichotomize continuous data


Statistics
• One sample tests
• Two groups tests
• SAM
• Several groups tests
• Linear modelling
• Linear modelling using user-defined design matrix
• Test proportions
• Correlate miRNA with target expression
• Correlate with phenodata
• Time series
• Association analysis
• Adjust p-values
• PCA
• DCA
• NMDS
• Sample size estimation
• Sample size calculations with an adapted BH method
• Up-down analysis of miRNA targets


Clustering
• KNN classification
• Hierarchical
• K-means
• K-means - estimate K
• Quality Threshold (QT)
• Classification
• SOM


Annotation
• Agilent, Affymetrix or Illumina genelist
• Add annotations to data
• Add genomic location to data
• Find miRNA targets
• miRNA annotations


Pathways
• Hypergeometric test for GO
• Hypergeometric test for KEGG or PFAM
• SAFE test for KEGG pathway enrichment
• Hypergeometric test for cytobands
• Gene set test
• GO enrichment for miRNA targets
• KEGG enrichment for miRNA targets
• Hypergeometric test for ConsensusPathDB


Promoter analysis
• Weeder
• Retrieve promoters


Copy number aberrations
• Import from GEO
• Import from CanGEM
• Normalize copy number data
• Plot copy number profiles
• Smooth waves from normalized aCGH data
• Segment copy number data
• Call aberrations from segmented copy number data
• Identify common regions from called copy number data
• Add cytogenetic bands
• Count overlapping CNVs
• Plot copy number aberration frequencies
• Count overlapping CNVs
• Plot copy number aberration frequences
• Count the number of aberrations per sample
• Cluster called copy number data
• Plot correlations of called copy number data
• Group tests for called copy number data
• Survival test for called copy number data
• Plot survival curves for called copy number data
• Fuse regions by column value
• Fuse regions manually
• Detect genes from called copy number data
• GO enrichment for called gene copy numbers
• Match copy number and expression features
• Plot profiles of matched copy number and expression
• Test for copy number induced gene expression
• Plot copy number induced gene expression
• Fetch probe positions from GEO
• Fetch probe positions from CanGEM


Visualisation
• Idiogram
• Chromosomal position
• Volcano plot
• Volcano plot from existing results
• Boxplot
• Dendrogram
• Histogram
• Correlogram
• Heatmap
• Annotated heatmap
  
  Utilities
• Search by correlation
• Search by gene name
• Search by genomic coordinates
• Filter by column
• Delete columns
• Delete and subtract columns
• Merge tables
• Merge data sets
• Merge expression and phenodata
• Extract genes from clustering
• Extract genes from GO term
• Extract genes from KEGG pathway
• Extract samples from table
• Extract genes using a p-value
• Extract genes
• Calculate fold change
• Average replicate chips
• Combine probes to genes
• Change interpretations
• Generate phenodata
• Calculate descriptive statistics
• Sort samples
• Sort genes
• Random Sampling
• Export tab2mage format
• Export GEO's SOFT format
• Import from GEO
• Import from ArrayExpress