RDML-consortium was founded to develop a universal
data format for real-time PCR data, named RDML (Real-time PCR Data
Markup Language). The intention to design an universal data
based on the experience that it is difficult to share qPCR data between
different laboratories and users, or exchange data between different
software packages or analysis tools.
problem is founded in the data collection software
packages that, depending on the company that provides these with their
instrument(s), save data in a proprietary format and allow to export
information in various file formats (.CSV, .TXT, .XLS), with different
layout and data field terminology.
common universal format would allow easy exchange of
raw annotated data between different laboratories. It would make it
possible to include qPCR data in scientific papers, allowing both
reviewers and readers to re-analyse the data, similar to the MIAME
guidelines propose for microarray experiments (Brazma et al., Nat
Genet., 2001; see publication below).
principle, the universal data format should contain
sufficient information to understand the experimental setup, re-analyse
the data and interpret the results. The data format is a flat text file
in Extensible Markup Language (XML), termed RDML, an acronym for "Real-time
PCR Data Markup Language". The file extension is *.rdml or
*.rdm. The format is independent of computer hardware, operating system
or available software package, and can be extended in the future to
include additional information if required.
can find the RDML schema here.
Dear LinRegPCR user,
We recently updated LinRegPCR to implement the import
and export of RDML files http://www.rdml.org
developed as a standard for export, exchange, and storage of
quantitative PCR data and is supported by several large qPCR system
suppliers as well as by data analysis software like qbase-plus.
LinRegPCR now forms a link between your qPCR system and such
statistical analysis software. LinRegPCR can handle RDML versions 1.0
and 1.1, as well as RDML files in which floating point values are
written with decimals points and decimal commas. LinRegPCR will write
the analysis results to an RDML file, version 1.1, with decimal points
to maintain compatibilty with the current RDML specification.
The RDML input option is the main
addition to LinRegPCR that was implemented in 2012. There were also
several qPCR systems added to the list of input formats from Excel
files. For other minor changes in the program, please have a look at
the recent updates listed on the LinRegPCR website (http://LinRegPCR.nl).
our site you will also find a link to a recent paper (Ruijter et al.,
Methods 2012), in which LinRegPCR and other publicly available PCR
amplification curve analysis programs were compared. This paper is
unique in the field of qPCR because all analysis methods were applied
by their original developers, and thus in the currently recommended
way. The paper was co-authored by the developers of these curve
analysis programs and members of the geNorm team, who performed the
statistical analysis. The datasets used for this comparison, and the
analysis results, can be downloaded from http://qPCRDataMethods.hfrc.nl.
hope you continue to enjoy the use of LinRegPCR.
wishes for the coming festive season and your future scientific
information about a microarray experiment (MIAME)-toward standards for
A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, Aach
W, Ball CA, Causton HC, Gaasterland T, Glenisson P, Holstege FC, Kim
V, Matese JC, Parkinson H, Robinson A, Sarkans U, Schulze-Kremer S,
Stewart J, Taylor R,
Vilo J, Vingron M.
Nat Genet. 2001
in: Nat Genet. 2001
Dec;29(4):373. Nat Genet. 2006 38(10):1089.
Bioinformatics Institute, EMBL outstation, Wellcome Trust Genome
Cambridge CB10 1SD, UK.
has become a widely used tool for the generation of gene expression
data on a
genomic scale. Although many significant results have been derived from
microarray studies, one limitation has been the lack of standards for
exchanging such data. Here we present a proposal, the Minimum
Information About a
Microarray Experiment (MIAME), that describes the minimum information
to ensure that microarray data can be easily interpreted and that
from its analysis can be independently verified. The ultimate goal of
work is to establish a standard for recording and reporting
expression data, which will in turn facilitate the establishment of
databases and public repositories and enable the development of data
With respect to MIAME, we concentrate on defining the content
of the necessary information rather than the technical format for