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limma (version 3.22.7)

Linear Models for Microarray Data

Description

Data analysis, linear models and differential expression for microarray data.

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Version

Monthly Downloads

413

Version

3.22.7

License

GPL (>=2)

Maintainer

Gordon Smyth

Last Published

February 15th, 2017

Functions in limma (3.22.7)

Topic: Hypothesis Testing for Linear Models

Turn a Microarray Data Object into a Matrix

Convert marrayNorm Object to an MAList Object

Barcode Enrichment Plot

beadCountWeights

Bead Count Weights for Illumina BeadChips

Test for Differential Splicing

Retrieve the Dimensions of an RGList, MAList or MArrayLM Object

Expression List - class

Empirical Bayes Statistics for Differential Expression

Prompt for Method Help Topics

Array Quality Weights

07.SingleChannel

Topic: Individual Channel Analysis of Two-Color Microarrays

anova.MAList-method

ANOVA Table - method

Average Over Irregular Replicate Probes

backgroundCorrect

Correct Intensities for Background

Set Status of each Spot from List of Spot Types

Multiple Testing Across Genes and Contrasts

Extract Log-Expression Matrix from MAList

Convert Gene Identifiers to Indices for Gene Sets

Test for Numeric Argument

Kooperberg Model-Based Background Correction for GenePix data

Merge RGList or MAList Data Objects

normalizeCyclicLoess

Normalize Columns of a Matrix by Cyclic Loess

normalizeMedianAbsValues

Normalize Columns of a Matrix to have the Median Absolute Value

Predictive log fold change for microarrays

Plot exons of differentially expressed gene

Plot Expression Densities

Print Leading Rows of Large Objects

rankSumTestWithCorrelation

Two Sample Wilcoxon-Mann-Whitney Rank Sum Test Allowing For Correlation

read.ilmn.targets

Read Illumina Data from a Target Dataframe

Read specified columns from a file

Read RGList or EListRaw from Image Analysis Output Files

Remove Common Extension from File Names

Moment Estimation of Scaled F-Distribution

Gene Ontology Analysis

Gene Ontology Analysis of Differentially Expressed Genes

intraspotCorrelation

Intra-Spot Correlation for Two Color Data

Two dimensional Moving Averages with 3x3 Window

Check for Full Column Rank

residuals.MArrayLM

Extract Residuals from MArrayLM Fit

trigammaInverse

Inverse Trigamma Function

Construct Matrix of Custom Contrasts

normalizeRobustSpline

Normalize Single Microarray Using Shrunk Robust Splines

Variance Stabilizing Normalization (vsn)

Multidimensional scaling plot of distances between gene expression profiles

plotPrintTipLoess

MA Plots by Print-Tip Group

Estimate Proportion of True Null Hypotheses

Trim Leading and Trailing White Space

protectMetachar

Protect Metacharacters

Read a GAL file

Read Header Information from Microarray Raw Data File

Rotation Gene Set Enrichment Analysis

Select Appropriate Linear Model

weighted.median

Weighted Median

Write MArrayLM Object to a File

Topic: Reading Microarray Data from Files

Topic: Background Correction

Between and within sums of squares for matrix

Combine RGList, MAList, EList or EListRaw Objects

Competitive Gene Set Test Accounting for Inter-gene Correlation

Limma Change Log

Retrieve the Dimension Names of an RGList, MAList, EList, EListRaw or MArrayLM Object

Correlation Between Duplicates

Construct Design Matrix

Merge two scans of two-color arrays

plotWithHighlights

Expected Signal Given Observed Foreground Under Normal+Exp Model

Write MA-Plots to Files

Identify Order in which Spots were Printed

Print Layout - class

Read Spot Types File

readImaGeneHeader

Read ImaGene Header Information

Subset RGList, MAList, EListRaw, EList or MArrayLM Objects

Summaries of Microarray Data Objects

Top Gene Set Testing Results from Romer

Top table of differentially spliced genes or exons

Unwrap Duplicate Spot Values from Rows into Columns

Eliminate Duplicate Names from the Gene List

05.Normalization

Topic: Normalization of Microarray Data

06.LinearModels

Topic: Linear Models for Microarrays

asMatrixWeights

asMatrixWeights

Area Under Receiver Operating Curve

Convert Individual Channel Design Matrix to M-A Format

Multiple Testing Genewise Across Contrasts

Extract Basic Data from Microarray Data Objects

Extract the Print Layout of an Array from the GAL File

Fit Linear Model to Microrray Data by Ordinary Least Squares

Linear Model for Series of Arrays

Make Values of Character Vector Unique

normalizeQuantiles

Normalize Columns of a Matrix to have the same Quantiles

normalizeForPrintorder

Print-Order Normalization

M-value, A-value Expression List - class

removeBatchEffect

Remove Batch Effect

Read Targets File

Table of Top Genes from Linear Model Fit

Topic: Diagnostics and Quality Assessment

10.GeneSetTests

Topic: Gene Set Tests

Convert Gene Aliases to Official Gene Symbols

Block Diagonal Matrix

tricubeMovingAverage

Moving Average Smoother With Tricube Weights

Transform RNA-Seq Data Ready for Linear Modelling

Convert Mean-Variance Trend to Observation-specific Precision Weights for Microarray Data

Topic: Analysis of RNA-seq Data

Between and within sums of squares

Get Numerical Spacing

fitGammaIntercept

Fit Intercept to Vector of Gamma Distributed Variates

Fit Linear Model to Microarray Data by Generalized Least Squares

LargeDataObject-class

Large Data Object - class

fitted.MArrayLM

Fitted Values Method for MArrayLM Fits

limmaUsersGuide

View Limma User's Guide

Fit Linear Model to Microrray Data by Robust Regression

normexp.fit.detection.p

Estimate Normexp Model Parameter Using Negative Controls Inferred from Regular Probes

normexp.fit.control

Normexp Model Parameter Estimation Aided by Negative Controls

Differential splicing plot

Pool Sample Variances with Unequal Variances

Spot Quality Weights

Squeeze Sample Variances

Student's t Quantile-Quantile Plot

Split Composite Names

Estimate Scale Factor in Mixture of t-Distributions

Table of Top GO Terms

voomWithQualityWeights

Combining observational-level with sample-specific quality weights for RNA-seq analysis

Lowess fit with weighting

01.Introduction

Introduction to the LIMMA Package

Turn a Microarray Linear Model Object into a Dataframe

Topic: Classes Defined by this Package

Average Over Replicate Arrays

arrayWeightsQuick

Array Quality Weights

Average Over Duplicate Spots

Compute Contrasts from Linear Model Fit

Reform a Design Matrix to that Contrasts Become Coefficients

Genuine Association of Gene Expression Profiles

Mean-rank Gene Set Test

Row and Column Positions on Microarray

Stemmed Heat Diagram

Image Plot of Microarray Statistics

Write Imageplots to Files

Fit Linear Model to Individual Channels of Two-Color Data

Univariate Lowess With Prior Weights

NormExp Background Correction and Normalization Using Control Probes

normalizeBetweenArrays

Normalize Between Arrays

normalizeWithinArrays

Normalize Within Arrays

Fit Normal+Exp Convolution Model to Observed Intensities

Plot of regularized linear discriminant functions for microarray data

Sigma vs A plot for microarray linear model

printtipWeights

Sub-array Quality Weights

Estimate Proportion of Expressed Probes

Read Illumina expression data directly from IDAT files

Read Illumina Expression Data

Red, Green Intensity List - class

Rotation Gene Set Tests

Convert Two-Color Targets Dataframe from One-Row-Per-Array to One-Row-Per-Channel

TestResults-class

Matrix of Test Results - class

Z-score Equivalents