Hands-on Application Workshops @GQ2023

Please direct your enquiry to our scientific organisation team, headed by Michael W. Pfaffl  GeneQuan.physio@ls.tum.de
 

The workshops are aimed at giving participants a deep and objective understanding of real-time quantitative PCR, digital-PCR, expression profiling, data analysis and their applications in various fields of molecular diagnostics. The courses are intended for academic or industrial researchers considering working with qPCR and/or dPCR or scientists currently working with these technologies who seek a deeper understanding.
All workshops offer extensive hands-on training by experts in the field.
Location:  Hans Eisenmann-Forum (HEF) for Agricultural Sciences
Thu 23rd to 24th March 2023    9:00 am - 5 pm

The workshop laboratories and seminar rooms are very close to the central lecture hall.

Workshop topics & short agendas:
               Seminar room 86-87 @ HEF
The workshops are hosted by:





In the "MicroRNA Analysis" and in the "Hands-on qPCR" workshops the qPCR data conversion, normalisation procedure, biostatistical calculations and the expression profiling will be done with the newest GenEx software by MultiD.
You can download a free trial version => Genex.Gene-Quantification.info

logo MultiD
The courses cover all aspects in quantititative PCR or digitl-PCR and take two days to complete. Each course is app. 40-50% hands-on and is limited to around 20 participants, resulting in very interactive teaching where everybody is given the opportunity to try the instrumentation. After visiting the course, participants will be able to plan and perform qPCR or digital-PCR experiments themselves, as well as anlyse and interpret the generated data.
Detailed course material and full catering (lunch, coffee, soft drinks and snacks) are included in the course fee.

Course dates                23rd & 24th March 2023               
Symposium & Workshop fees
Course starts at            9 am     
Course ends around    5 pm

Please register for the Symposium & Workshops using the ConfTool registration platform => https://www.conftool.com/GQ2023/


Workshop short agendas:

Digital PCR  (2-days)  hosted by Bio-Rad
Seminar room 82 @ HEF

Description:
Digital PCR is a technology that is gaining momentum in multiple areas of nucleic acid analysis. This course introduces the user to digital PCR technology with a solid review to the theory, overview of classic and new applications, hands on wet chemistry experiments (absolute quantitation, copy number variation and rare event detection, multiplex gene expression), data analysis and math and stats related to dPCR.


Day 1

•    Welcome and Introductions
•    Introduction to Digital PCR
•    Experimental reaction setup
•    CNV and absolute quantification experiment (wet)
•    ABS, CNV and RED applications overview
•    Data collection for ABS and CNV experiment
•    RED and multiplex GE experiment (wet lab)
•    ABS and CNV results analysis
•    Data collection for RED experiment
•    Review of the day
Day 2

•    dPCR assay design and optimization
•    ddPCR -- basic statistics
•    RED results analysis
•    Basic and advanced multiplexing
•    Review of advanced ddPCR applications
•    When qPCR and when ddPCR? Moving from qPCR to ddPCR
•    Open Q&A session
•    Review of the workshop




Basic hands-on qPCR  (2-days)  hosted by TATAA Biocenter
Seminar room 85 @HEF

Target Audience
Researchers interested in analyzing nucleic acids

Experience Qualifications
Basic knowledge about DNA & RNA and molecular analyses

Description
This is a basic real-time qPCR course for people starting with qPCR or is working with the technique and want to understand it deeper. The course starts with describing how the technology works, different types of detection technologies and instruments. Then you will learn how to design primers and probes and optimize new assays. You will get an understanding of the qPCR reaction so you are able to troubleshoot and improve your own experiments. During the first day a standard curve hands-on experiment will be performed where we will practically show how to evaluate amplification curves and handle qPCR instrument software.
The second day will cover how to do relative quantification with qPCR, how to find stable reference genes and do proper normalization. Several quantification examples will be demonstrated with calculations of ΔCq, ΔΔCq and efficiency corrected ratios. During hands-on lab you will receive relative quantification data that you will perform calculations with yourself with a few different methods. You will get an understanding of how Cq-values, thresholds and efficiency affect your quantification results. During the day you will also learn how to do absolute quantification, work with standard curves and how to properly validate your qPCR assay performance.

Day 1

Introduction to PCR and qPCR
    - How does qPCR work?
    - Different detection chemistries, dyes or probes?
    - Different applications for qPCR

qPCR data evaluation
    - How does qPCR software process the data
    - How to evaluate curves and set threshold

Primer and probe design
    - How to do proper primer design
    - How to avoid primer dimer formation
    - Other important considerations for primer design
    - How to design hydrolysis probes
    - Practical exercises in primer design

Optimization of qPCR protocols
    - Which factors affect the PCR?
    - Which factors can be optimized?


Hands-on lab running qPCR analyzing unknown samples with standard curve.

Day 2

Normalization
    - Different ways to normalize
    - How to find stable reference genes

Basic quantification theory
    - Quantification methods and equations
    - How to do interplate calibration

Absolute quantification strategies
    - How to do absolute quantification
    - What is a suitable standard?

Validation of assays
    - How to determine LOD and LOQ
    - Precision estimation
    - Which controls should be used?

Quantification calculation examples 
    - Practical examples with relative quantification calculations
    - Calculations with own generated qPCR data

Hands-on lab running qPCR and calculating relative quantities with different strategies. 




MicroRNA Analysis  (2-days)  hosted by TATAA Biocenter & MultiD
Seminar room 86-87 @ HEF

Target Audience
Researchers interested in analyzing microRNA

Experience Qualifications
Basic knowledge about microRNA and molecular analyses

Description
This course introduces miRNA and its variant forms. Methods to extract and purify microRNA and prepare it for analysis, including quality control. Methods for microRNA expression analysis are presented and compared, to learn how to choose the best method for each study. Analysis of microRNA data is also discussed, including challenging normalization.

Day 1

    · MicroRNA background including biogenesis and function
    · MicroRNA extraction – sampling, miRNA stability, extraction kit comparison
    · Quality control of miRNA
    · MicroRNA and liquid biopsies – challenges of miRNA analysis in biofluids

Hands-on lab testing of quality and quantity of miRNA



Day 2

    · MicroRNA quantification with microarray, nanoString, NGS and RT – qPCR methods
    · Comparison of miRNA quantification methods
    · Experimental design and data analysis
    · RT-qPCR normalization of miRNA data
    · Introduction to NGS data analysis

Hands-on lab of miRNA RT-qPCR analysis including data analysis in Genex
 



Web-based qPCR data analysis  (1-day)  hosted by Dr A Untergasser, Dr MJB van den Hoff and Dr JM Ruijter
Unbiased platform-independent analysis of qPCR data - from fluorescent data to publishable graph.
Seminar room 88 @ HEF

Target Audience
Advanced qPCR users interested in measuring nucleic acid levels using DNA binding dyes

Experience Qualifications
Experience in analyzing qPCR data beyond the Cq

Description
The “Web-based qPCR data analysis” workshop includes the analysis of amplification and melting curves, calculation of efficiency-corrected target quantities, reference gene validation, between-run correction and basic statistical comparison of groups of biolgoical replicates. This workshop uses the web-based qPCR data analysis pipeline implemented in the RDML-tools. You can find the free RDML-tools  => RDML-tools

Though discussed for two decades, the Covid pandemic has univocally illustrated the poor interlaboratory reproducibility of RT-qPCR results reported as just Cq (or Cp or Ct) values. Although integrating the PCR efficiency in the analysis has been shown to overcome most of this problem, its application was never considered essential. Moreover, determining the PCR efficiency seemed to require extra reactions and analysis steps. To overcome this limitation, a free, fast, assumption-free, platform-independent, and publicly available integrated pipeline for the analysis of qPCR experiments was developed. This set of tools, based on earlier papers and programs of our group, is based on the RDML platform and hosted on the EMBL server. Upon input of the raw fluorescence data, the amplification curve and melting curve of each individual qPCR reaction are analyzed automatically and interactively, and for each individual reaction the efficiency-corrected starting concentration of the target is reported. A comprehensive error assignment flags reactions and assays that do not conform the criteria for positive and negative controls. Optionally, statistical outlier detection can be applied to identify deviant replicates. Moreover, the platform holds tools to identify valid references genes and to remove between-plate variation in multi-plate qPCR experiments. Target quantities per reaction can then be converted into normalized and relative expression levels according to the experimental design and bar graphs, including data points per reaction, can be drawn. The 1-day workshop will provide you with the skills to analyze qPCR runs in an unbiased way and present the efficiency-corrected results in graphs or in spreadsheets for further analysis. The workshop will consist of short background lectures and extensive hands-on exercises which you will run on your own laptop.

Program Thursday March 23, 2023 from 9.00 to 17.00

1: Basics on amplification curve analysis (9.00-10.00)
Theory:  Basics of amplification curve analysis, with PCR Efficiency determination from the exponential phase and calculation of the efficiency-corrected target quantity (N0) per reaction (with Nq, Cq and mean E)
Hands-on:  Using RDML-LinRegPCR with a provided RDML-data file to get acquainted with the RDML-tools

2: Basics on melting curve analysis (10.15-11.15)
Theory:  Basics on melting curves analysis and the option to correct N0 with the fraction fluorescence in the correct melting peak
Hands-on:  Using RDML-Melting curve analysis with a provided RDML-data file to evaluate the effect of the applied procedure

3: Between plate correction (11.30-12.30)
Theory:  How to determine the multiplicative factor per plate and remove the systematic between-plate variation
Hands-on:  Using RDML-LinRegPCR to analyze two runs within one experiment and using RDML-Merge to merge the data into one experiment from which the systematic between-plate variation is removed

4: Import of data into RDML (13.30-14.30)
Theory:  RDML structure; from RDML output of the thermocycler to compiling an RDML-dataset from these raw fluorescence data
Hands-on:  Using RDML-Edit and RDML-TableShaper to illustrate the file structure, to adapt the format and to create an RDML file using example data from different qPCR machines

5: Reference gene identification (14.45-15.45)
Theory:  The need for reference genes and how to identify reference genes using RDML-geNorm
Hands-on:  Using RDML-LinRegPCR and RDML-geNorm to identify a set of valid reference genes

6: From qPCR run to results graph and statistics (16.00-17.00)
Theory:  How to apply reference genes
Hands-on:  Using RDML-LinRegPCR, RDML-Bargraph and RDML-Statistics with a provided data set you will perform the full analysis from raw fluorescent data till the presentation of the results in a publishable graph



Please direct your enquiry to our scientific organisation team, headed by Michael W. Pfaffl   GeneQuan.physio@ls.tum.de

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