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NormqPCR

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.

OLIVER / OLIgonucleotide Variable Expression Ranker

A software tool for identifying reference genes from large datasets. This tool compiles eight different methods and had been incorporated as part of Bactome project. OLIVER is dependent on Collection of Python Algorithms and Data Structures (COPADS). In addition, OLIVER can be used to determine the stability of each gene in the large-scale dataset. A ranking of the genes in each dataset was obtained, with the lowest ranking gene having the greatest invariance. This software can be used as alternatives to NormFinder, geNorm, and BestKeeper.