HTqPCR

This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information.

This package is for version 3.20 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see HTqPCR.

Automated analysis of high-throughput qPCR data

Bioconductor version: Release (3.20)

Analysis of Ct values from high throughput quantitative real-time PCR (qPCR) assays across multiple conditions or replicates. The input data can be from spatially-defined formats such ABI TaqMan Low Density Arrays or OpenArray; LightCycler from Roche Applied Science; the CFX plates from Bio-Rad Laboratories; conventional 96- or 384-well plates; or microfluidic devices such as the Dynamic Arrays from Fluidigm Corporation. HTqPCR handles data loading, quality assessment, normalization, visualization and parametric or non-parametric testing for statistical significance in Ct values between features (e.g. genes, microRNAs).

Author: Heidi Dvinge, Paul Bertone

Maintainer: Heidi Dvinge <hdvinge at fredhutch.org>

Citation (from within R, enter citation("HTqPCR")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("HTqPCR")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation


Reference Manual	PDF

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	DataImport, DifferentialExpression, GeneExpression, MicrotitrePlateAssay, MultipleComparison, Preprocessing, QualityControl, Software, Visualization, qPCR
Version	1.60.0
In Bioconductor since	BioC 2.5 (R-2.10) (15 years)
License	Artistic-2.0
Depends	Biobase, RColorBrewer, limma
Imports	affy, Biobase, gplots, graphics, grDevices, limma, methods, RColorBrewer, stats, stats4, utils
System Requirements
URL	http://www.ebi.ac.uk/bertone/software

Suggests	statmod
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Build Report	Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository	git clone https://git.bioconductor.org/packages/HTqPCR
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/HTqPCR
Package Short Url	https://bioconductor.org/packages/HTqPCR/
Package Downloads Report	Download Stats