[Bioforum] qPCR NEWSLETTER - April 2007

Editor www.Gene-Quantification.info via bioforum%40net.bio.net (by editor from gene-quantification.info)
Thu Apr 26 03:49:04 EST 2007

qPCR NEWSLETTER - April 2007

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Dear researcher,
dear Gene Quantification page reader,

Our newsletter informs about the latest news in quantitative real-time
PCR (qPCR and qRT-PCR), which are compiled and summarised on the Gene
Quantification homepage. The focus of this newsletter issue is:

- Cluster analysis in real-time PCR
- Error propagation in PCR
- Update of the qPCR Talk and Webinar page
- Online or invisible!
- Real time open qPCR course from 21th - 25th May 2007 at the TATAA
Biocenter Prague
- Real time open qPCR course from 2nd - 6th July 2007 in Freising,


Clustering is often one of the first steps in gene expression
analysis. How do clustering algorithms work, which ones should we use
and what can we expect from them?

Our ability to gather genome-wide expression data has far outstripped
the ability of our puny human brains to process the raw data. We can
distill the data down to a more comprehensible level by subdividing
the genes into a smaller number of categories and then analyzing
those. This is where clustering comes in.
The goal of clustering is to subdivide a set of items (in our case,
genes) in such a way that similar items fall into the same cluster,
whereas dissimilar items fall in different clusters. This brings up
two questions: first, how do we decide what is similar; and second,
how do we use this to cluster the items? The fact that these two
questions can often be answered independently contributes to the
bewildering variety of clustering algorithms.
Gene expression clustering allows an open-ended exploration of the
data, without getting lost among the thousands of individual genes.
Beyond simple visualization, there are also some important
computational applications for gene clusters. For example, Tavazoie et
al. used clustering to identify cis-regulatory sequences in the
promoters of tightly coexpressed genes. Gene expression clusters also
tend to be significantly enriched for specific functional categories—
which may be used to infer a functional role for unknown genes in the
same cluster.
In this primer, I focus specifically on clustering genes that show
similar expression patterns across a number of samples, rather than
clustering the samples themselves (or both). I hope to leave you with
some understanding of clustering in general and three of the more
popular algorithms in particular. Where possible, I also attempt to
provide some practical guidelines for applying cluster analysis to
your own gene expression data sets.


- How does gene expression clustering work?
- Evaluation of gene-expression clustering via mutual information
distance measure.
- How to infer gene networks from expression profiles.
- Distribution-insensitive cluster analysis in SAS on real-time PCR
gene expression data of steadily expressed genes.
- A new molecular breast cancer subclass defined from a large scale
real-time quantitative RT-PCR study.
- Transcriptional regulatory network analysis of developing human
erythroid progenitors reveals patterns of coregulation and potential
transcriptional regulators.
- An approach for clustering gene expression data with error
- Expression profiles and biological function.
- Smoking and cancer-related gene expression in bronchial epithelium
and non-small-cell lung cancers.


Error propagation in PCR:


- A general model of error-prone PCR.
- Error propagation in relative real-time reverse transcription
polymerase chain reaction quantification models: The balance between
accuracy and precision.
- A quantitative model of error accumulation during PCR
- Real Time PCR:  A useful new approach?  Statistical Problems?


Power Calculator - NEW links !

This article focuses on how to do meaningful power calculations and
sample-size determination for common study designs. There are 3
important guiding principles. First, certain types of retrospective
power calculations should be avoided, because they add no new
information to an analysis. Second, effect size should be specified on
the actual scale of measurement, not on a standardized scale. Third,
rarely can a definitive study be done without first doing a pilot
study. Some simple examples as well as a complex example are given.
Power calculations are illustrated using Java applets developed by the



TALKS Update of the qPCR Talk and Webinar page

A lot of interesting TALKs, WEBINARs, SLIDE SHOWs, and PODCASTs from
various speakers, companies, qPCR Events, and journals (Nature and
Science) are FREE for download. Have a look and you will definitely
something interesting for your scientific work !




CITATION Online or invisible!

Articles freely available online are more highly cited. For greater
impact and faster scientific progress, authors and publishers should
aim to make research easy to access.



Real time open qPCR course from 21th - 25th May 2007 at the TATAA
Biocenter Prague



TATAA Biocenter Germany - qPCR Application workshops


At the TATAA Biocenter Germany we offer qPCR application workshops,
the 3-day Core Module and a 2-day Biostatistics Module.  qPCR courses
are held in regularly in Göteborg, Sweden in English and in Freising-
Weihenstephan, Germany in German and English. Depending on the
occasion the workshop language and the different prices may apply.
Further customized workshops and specialized trainings will be held as
well across Europe and world-wide. TATAA Biocenter Germany courses are
held in cooperation with the Institute of Physiology, located at the
Technical University of Munich, in Freising-Weihenstephan, near
Munich, very close to the Munich Airport (MUC). For more information
and to register for the qpCR application workshops, please see our web
page:  http://tataa.gene-quantification.info/

Course Occasions 2007:         Please register here:    http://www.tataa.com/

- 2nd - 6th July (in English)   3-day Core module and 2-day
BioStatistics Module


Forward Please send the qPCR NEWS to further scientists and friends
who are interested in qPCR and in our Academic & Industrial
Information Platform for qPCR.

Best regards,

Michael W. Pfaffl
responsible Editor of the Gene Quantification Pages

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