Digital PCR is an extremely promising method for increasing accuracy, precision and sensitivity of nucleic acid quantification beyond the capabilities of traditional real-time qPCR. This is done by combining PCR assays with single molecule sensitivity with a system to partition a sample into a set of reactions which number close to, or more than, the total number of target molecules in that sample. The combination of these functions makes it possible to calculate the number of target molecules present by counting the number of reactions with or without amplification. Many novel applications are enabled by this new approach, including reference free absolute quantification and high sensitivity rare-allele quantification. We will be presenting a live demonstration of the QuantStudio™ 3D Digital PCR System, a new digital PCR platform from Life Technologies™. This chip based system enables collection of up to 20,000 data points per sample run. The workflow has been optimized for simplicity, minimizing hands-on time, minimizing the risk of sample cross contamination, and minimizing sample loss. In this workshop, we will review the basics of digital PCR theory and practice, discuss the capabilities of the QuantStudio™ 3D Digital PCR System, and demonstrate the steps involved in a full digital PCR experiment, including chip loading, running, imaging and data analysis.
Mikael Kubista1,2, Amin Forootan2,3, Björn Sjögren3,4
1TATAA Biocenter, Sweden; 2MultiD Analyses AB; 3Goteborg University; 4Lawrence Livermore National Laboratory
As qPCR is becoming mature technology with widespread use requirements on validation, quality assessment and reporting increases. This is particularly important when data are submitted for approval by regulatory bodies, reported to clients, or published in quality journals. For molecular diagnostic applications this includes determining PCR efficiency with confidence intervals, establishing the linear range of the assay, its limit of quantification, limit of detection and random error. For routine applications also estimates of repeatability and reproducibility may be relevant. For the samples analyzed estimated target concentrations shall be indicated with confidence intervals. These analyses are recommended by the Clinical and Laboratory Standards Institute. In my presentation I will show how these analyses are performed on qPCR using GenEx.
Goal of expression profiling is to explain biological phenomena. Workflow starts by planning, designing and optimizing an experiment, collecting the data, analyzing the data, and extracting biological information. Typically large amounts of data are collected that are batch imported and pre-processed to remove variation between runs, reduce intersubject variation, and minimize technical noise. Missing data are also handled. The data are then analyzed using powerful multivariate statistical methods including hierarchical clustering, principal component analysis (PCA), and self-organized maps. Dynamic PCA is used for variable selection to identify the most relevant genes explaining the observations. Finally, the data are passed from GenEx for cloud based pathway analysis with the Ingenuity iReport. In will present seamless workflow from the collection of data to the extraction of biological information using GenEx.
Download a free GenEx trial version on GenEx.gene-quantification.info
Genomatix Software GmbH, Germany
The ongoing evolution of Next Generation Sequencing is revealing ever more of the complexity of genomes, gene expression, and gene regulation. To harness the considerable potential of this technology for creating biologically relevant information, data generation must be matched by analysis tools and strategies which integrate and consolidate the available lines of evidence into scientifically interpretable results.
This talk provides an overview of the solutions offered by Genomatix for the analysis of Next Generation Sequencing data.
The presentation will focus on the following analysis methods:
Assessment of genomic variants; Expression and transcript fusion analysis; Examination of regulatory features: protein-DNA binding and DNA methylation; Data integration employing positional correlation, genome annotation, biological classification, regulatory pathways, and gene networks
Examples will include the application of the above to the study of cancer, the identification of the basis of hereditary diseases, and the elucidation of disease-relevant regulatory networks.
Are you struggling to get your qPCR data-analysis right? Do you want to speed up your analysis?
Join Barbara D’haene, PhD, for a lunch talk and get access to qbasePLUS.
During this session Barbara will show how to analyse a qPCR experiment using qbasePLUS. The key points demonstrated will be quality control, normalization and easy biostatistical analysis.
qbasePLUS is based on the proven geNorm and qBase technology. The software is developed at Biogazelle by recognized qPCR experts Jo Vandesompele and Jan Hellemans. Biogazelle is a young and dynamic PCR company, eager to accelerate the discoveries in the PCR community.