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**MAMA**: Meta-Analysis of MicroArray**MetaArray**: Class "MetaArray" ~~~

# Class "MetaArray" ~~~

### Description

A class created for meta-analysis of microarray

### Objects from the Class

Objects can be created by calls of the form `new("MetaArray", ...)`

.

### Slots

`GEDM`

:Object of class

`"list"`

- gene expression data matrices are stored in individual slot of the list. Each matrix refer to one dataset, genes are represented in rows, samples in columns.`clinical`

:Object of class

`"list"`

- clinical data matrices, clinical description of samples, rows refer to samples, columns to clinical characteristics`datanames`

:Object of class

`"character"`

- vector of names of the datasets

### Methods

- plot
`signature(x = "MetaArray", y = "missing")`

: draws distribution of clinical variables of several datasets. Boxplot is drawn for numerical variables and barplot for categorical ones.`signature(x = "MetaArray")`

: prints the number of samples and genes in each dataset, followed by summarization of each clinical characteristic of the samples- show
Same as

`print`

- as.list
Function transforms a MetaArray object into a list, in which each slot is again a list of three slots: gene expression data matrix

`GEDM`

, clinical data`clinical`

, name of the dataset`dataname`

### Author(s)

Ivana Ihnatova

### Examples

1 | ```
showClass("MetaArray")
``` |

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- clinical: Functions to retrieve and assign
- clinical: Functions to retrieve and assign
- clinical.sum: Function to calculate summaries of clinical data
- clinical.sum: Function to calculate summaries of clinical data
- colIntersect: Function to find intersect in columns of a data.frame
- colIntersect: Function to find intersect in columns of a data.frame
- ColonData: Example dataset for meta-analysis of microarray
- ColonData: Example dataset for meta-analysis of microarray
- commonGenes: Function to compute number of common genes in ordered gene...
- commonGenes: Function to compute number of common genes in ordered gene...
- computeAlpha: Function to do compute tunning parameter alpha
- computeAlpha: Function to do compute tunning parameter alpha
- computeOrdering: Function to compute ordered gene lists
- computeOrdering: Function to compute ordered gene lists
- compute.RQ: Function to compute R and Q statistics as defined in - see...
- compute.RQ: Function to compute R and Q statistics as defined in - see...
- conting.tab: Contingency table from gene lists
- conting.tab: Contingency table from gene lists
- cv.filter: Microarray probes filtering
- cv.filter: Microarray probes filtering
- entitybuild2: Function to calculate test statistic for microarray data
- entitybuild2: Function to calculate test statistic for microarray data
- ES.GeneMeta: Wrapper function for combining the effect size as implemented...
- ES.GeneMeta: Wrapper function for combining the effect size as implemented...
- flip: Function to flip data frames
- flip: Function to flip data frames
- fold.change: Function to do compute fold change between two groups
- fold.change: Function to do compute fold change between two groups
- gene.list: Intersect of gene lists
- gene.list: Intersect of gene lists
- gene.select.FC: Function to select genes according to fold change
- gene.select.FC: Function to select genes according to fold change
- join.DEG: Function to join vectors of differentially expressed genes to...
- join.DEG: Function to join vectors of differentially expressed genes to...
- join.results: Function to join results from meta-analysis to one list
- join.results: Function to join results from meta-analysis to one list
- make.matrix: Function to make matrix for heatmap to compare results of...
- make.matrix: Function to make matrix for heatmap to compare results of...
- MAP.genes: Function to do assign probesets IDs to patterns
- MAP.genes: Function to do assign probesets IDs to patterns
- MAP.Matches: Wrapper function for MAP-Matches method
- MAP.Matches: Wrapper function for MAP-Matches method
- MAPmatrix: Function to summarize binary matrix
- MAPmatrix: Function to summarize binary matrix
- MAPsig1: Pattern signifficance
- MAPsig1: Pattern signifficance
- MAPsig2: Pattern signifficance
- MAPsig2: Pattern signifficance
- MCtest: Monte Carlo permutation test
- MCtest: Monte Carlo permutation test
- mergedata: Function to merge data from MetaArray object
- mergedata: Function to merge data from MetaArray object
- MetaArray: Class "MetaArray" ~~~
- MetaArray: Class "MetaArray" ~~~
- metagene: Function to do extract row from list of data.frames
- metaheat: Display Data as Heatmap
- metaheat: Display Data as Heatmap
- metaheat2: Function to plot heatmap
- metaheat2: Function to plot heatmap
- metalist.to.matrix: Function to do convert list to matrix
- metalist.to.matrix: Function to do convert list to matrix
- metaMA: Wrapper function for effect size or p-value combination...
- metaMA: Wrapper function for effect size or p-value combination...
- meta.test: Function to compute T-statistic and p-value in meta-analysis
- meta.test: Function to compute T-statistic and p-value in meta-analysis
- methods: Replacement Methods for 'MetaArray' object
- methods: Replacement Methods for 'MetaArray' object
- METRADISC: Wrapper function for METRADISC method
- METRADISC: Wrapper function for METRADISC method
- patternMatch: Function to count soft pattern matches
- patternMatch: Function to count soft pattern matches
- patternMatch.strong: Function to count strong pattern matches
- patternMatch.strong: Function to count strong pattern matches
- patternmatrix: Function to split binary vectors to matrix.
- patternmatrix: Function to split binary vectors to matrix.
- patternToString: Function to convert rows of a matrix to strings
- patternToString: Function to convert rows of a matrix to strings
- performSOGL: Function to perform analysis using Similarity of Ordered Gene...
- performSOGL: Function to perform analysis using Similarity of Ordered Gene...
- plotES: Function to do plots in combination of effect size method
- plotES: Function to do plots in combination of effect size method
- plotgene: Function to visuaze change in expression of one gene
- plotgene: Function to visuaze change in expression of one gene
- plotgene2: Function to visuaze change in expression of one gene
- plotgene2: Function to visuaze change in expression of one gene
- plotpattern: Function to do plot signifficance of Meta-Analysis Patterns
- plotpattern: Function to do plot signifficance of Meta-Analysis Patterns
- plotQvsChi: Function to plot quantiles of Cochran's Q statistic and...
- plot.SOGLresult: Function to plot an object of class SOGLresult
- plot.SOGLresult: Function to plot an object of class SOGLresult
- prelimScore: Function compute preliminary Similarity Score for Ordered...
- prelimScore: Function compute preliminary Similarity Score for Ordered...
- prepareData: Function to prepare data
- prepareData: Function to prepare data
- preparePermutations: Function to prepare permutation and subsamples
- preparePermutations: Function to prepare permutation and subsamples
- probs.to.matrix: Function to convert list to matrix
- probs.to.matrix: Function to convert list to matrix
- RandomScore: Function to do compute random and subsampled similarity score
- RandomScore: Function to do compute random and subsampled similarity score
- rank.genes: Rank genes
- rank.genes: Rank genes
- rank.genes.adv: Function to rank genes
- rank.genes.adv: Function to rank genes
- RankProduct: Wrapper function for RankProduct method
- RankProduct: Wrapper function for RankProduct method
- ratio: Function to calculate the ratio of co-significant:...
- ratio: Function to calculate the ratio of co-significant:...
- sd.filter: Microarray probes filtering
- sd.filter: Microarray probes filtering
- selectAlpha: Function to select the most optimal alpha parameter
- selectAlpha: Function to select the most optimal alpha parameter
- selectClass: Function to select class labels from MetaArray object
- selectClass: Function to select class labels from MetaArray object
- selectGenes: Function to select genes that account for Similarity score
- selectGenes: Function to select genes that account for Similarity score
- sigScore: Function to calculate signifficance of similarity score
- sigScore: Function to calculate signifficance of similarity score
- test.group.shuffle: Function to do compute test statistic iterativelly
- test.group.shuffle: Function to do compute test statistic iterativelly
- T.select: Function to help with selection of threshold for T-statistics
- T.select: Function to help with selection of threshold for T-statistics
- VennMapper: Wrapper function for VennMapping
- VennMapper: Wrapper function for VennMapping
- Z: Function to compute Z-statistics in contingency table
- Z: Function to compute Z-statistics in contingency table
- zScores: Function for Meta-analysis of gene expression data
- zScores: Function for Meta-analysis of gene expression data