Handles information derived from CFX systems for polymerase chain reactions (PCR) detection. CFX Manager is a standalone software dedicated to perform analysis for single nucleotides polymorphisms (SNPs) genotyping studies, as well as gene expression. Besides, the application is able to generate a wide range of plots and includes functions for data analysis that can be customized according the user needs.
The ddCt Algorithm is an approximation method to determine relative gene expression with quantitative real-time PCR (qRT-PCR) experiments. Compared to other approaches, it requires no standard curve for each primer-target pair, therefore reducing the working load and yet returning accurate enough results as long as the assumptions of the amplification efficiency hold. The ddCt package implements a pipeline to collect, analyse and visualize qRT-PCR results, for example those from TaqMan SDM software, mainly using the ddCt method. The pipeline can be either invoked by a script in command-line or through the API consisting of S4-Classes, methods and functions.
A package for the R statistical computing environment, to enable the processing and analysis of qPCR data across multiple conditions and replicates. HTqPCR performs quality assessment, normalization, data visualization and statistical significance testing for Ct values between features (genes and microRNAs) across multiple biological conditions, such as different cell culture treatments, comparative expression profiles or time-series experiments. As it is R based, HTqPCR runs on different operating systems and is easy to incorporate into an analysis pipeline, or used in conjunction with other tools available through the Bioconductor project.
Assists in modeling and imputing non-detects in the results of Quantitative real-time PCR (qPCR) experiments. nondetects allows users to manage a variety of study designs. It contains two methods to handle qPCR non-detects that provide consistent estimates of the first and second moments of gene expression: MI and DirEst. MI takes into account the uncertainty of the imputed data, and DirEst permits one to directly estimate within replicate means and variances for each gene and sample type.
Allows users to analyze single-cell gene expression experiments. Monocle can realize differential expression analysis, clustering, visualization, and other useful tasks on single-cell expression data. The software enjoins individual cells according to a defined progress through a biological process, without knowing ahead of time which genes define progress through that process. It is designed to work with RNA-Seq and quantitative polymerase chain reaction (qPCR) data, and implements Census and BEAM tools.
Provides tools for uploading RT-qPCR data into R, looks for the optimal reference genes, and normalises the data using the ΔΔCq method. NormqPCR allows the user to read RT-qPCR data into R, to deal with undetermined Cq values, to find a suitable reference gene or genes for a given experiment using a method for optimal reference gene selection and to normalise the data via the ΔCq and 2−ΔΔCqnormalisation methods. The user can also use a number of existing bioconductor packages and functions to perform quality control on their data, and can check the adequacy of reference genes visually. Implementing popular optimal reference gene finding algorithms as NormqPCR in the widely-used statistical software for genomic analysis, R, represents an important contribution to the RT-qPCR community, and increases the available options for the analysis of this type of data.
Offers functionalities for investigating real-time quantitative polymerase chain reaction (PCR) data at SIRS-Lab GmbH. SLqPCR can be used to normalize real-time quantitative reverse transcriptase polymerase chain reaction (RT-PCR) data. It employs the estimation of a set of reference/housekeeping (HK) genes for gene expression experiments to work.