CLC Genomics Workbench 12 and Ingenuity Variant Analysis (IVA) & Ingenuity Pathway Analysis (IPA) Training

Course date: 29 April 2019 - 30 April 2019
Location: Erasmus MC, Ee 15.28

Click here to register for this course

(1st day)

One-day hands-on training workhop by the team from Qiagen about the CLC Genomics Workbench 12  and Ingenuity Variant Analysis (IVA).

This hands-on training workshop will introduce users to the CLC Genomics Workbench 12 (https://www.qiagenbioinformatics.com/products/clc-genomics-workbench) for the fast and efficient processing and visualisation of Human NGS data, and to Ingenuity Variant Analysis (https://www.qiagenbioinformatics.com/products/ingenuity-variant-analysis/) for the identification, prioritisation and biological interpretation of DNA Variants. The case study will cover the basics of data visualisation, QC, the creation of user-constructed workflows, and the identification of variants from targeted human DNA resequencing using the Workbench. The biological significance of the variants will then be interpreted using Ingenuity Variant Analysis which will allow users to additionally annotate, filter and prioritise variants based on their biological relevance.

Topics

Introduction to QIAGEN Sample to Insight, CLC Genomics Workbench 12 and Ingenuity Variant Analysis

  • Getting Started with the CLC Genomics Workbench 12

  • Loading human fastq data and performing QC

  • Alignment of reads to a Reference genome, coverage and QC

  • Variant Calling and variant-level annotation

  • Workflows for different data types

  • Integrating the Workbench with Ingenuity Variant Analysis

  • Creating an Analysis of multiple samples in Variant Analysis

  • Biological interpretation of variants

  • Refining filters, refining the analysis

  • Advanced Analysis Tips and Tricks

Time Schedule:

Coffee

9.30

Coffee break 10.45

Lunch 12.30

Start 13.15

Coffee 14.30

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(2nd Day)

Ingenuity Pathway Analysis (IPA) Training

This hands-on training workshop will introduce new users to Ingenuity Pathway Analysis (https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis/) for the biological interpretation of ‘omic data, and provide additional information for inexperienced users of the system. The training will use an RNA-Seq data set as a case study. For example, the transcriptional changes observed in hepatocellular carcinomas in comparison to paired normal liver tissue. The course will also highlight the considerations when analysing and integrating other data types such as proteomics or metabolomics data, and will touch on the analysis of miRNA.

Course Topics:

  • Introduction to QIAGEN Sample to Insight and Ingenuity Pathway Analysis (IPA)
  • Uploading data and running a Core Analysis
  • Interpreting a Core Analysis
    o Canonical Pathways Analysis
    o Upstream Regulator Analysis
    o Downstream Effect Analysis
    o Molecular Network Analysis
  • Search & Pathway Building; Search & Explore case study
  • Comparison Analysis & Analysis Match
  • Sharing & Collaboration
  • Best Practice Tips & Tricks
  • Overview of other IPA analysis tools
Time Schedule:

Coffee from 9.15

Start 

9.30

 

Coffee break 10.45

Lunch 12.30

Start 13.15

Coffee 14.30

You can register for each single day, or for both days.
 
ECTS: 0,3/day
 
Teachers: Kim Madsen & André Koper, QUIAGEN
 
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Attendance fee
The subscription fee of non-commercial participants for the Course is €200 per day; 2 days €350.
•All participants from the Postgraduate School MolMed get a discount of 100 % 
•PhD students and research master students have 50% discount 
•Research master students who pay it themselves have 75% discount
We will send you an invoice (if applicable) after attending the course.
•If there is personal budget left, you need to use this in order to pay. Otherwise, IF you are a MolMed member you can participate for free.

ECTS 
0,3 ECTS per day;


General information
Financial regulation of the Postgraduate School MolMed

From January 1st, 2019 the following financial rules apply, but they may differ per course still. Look at the course fee of each course to be sure which discounts are really applied:

Non-commercial course, symposium or workshop fee: €200/day, €350/2days, €750/week.

• Participants of the postgraduate school MolMed: discount of 100%

• However, the Research Management course and the workshops Photoshop/Illustrator/Indesign have to be paid from the ‘personal budget’ of employees, MolMed members and PhD students included. So they will receive an invoice from us which you have to pay and which will be reimbursed by your Department. When you will pay from your personal budget you need to provide us your home address details for the invoice

• PhD students and Master’s students, regardless of institution: discount of 50%.

  • The course fees of research master’s students will be paid by their master program at rate of €100/ECTS. For not I&I master students: please inform your master program in advance whether they agree to pay.
  • Master’s students who are paying the fee from their private budget: discount of 75%. When you will pay from your personal budget you need to provide us your home address details for the invoice.
  • However, 2 courses in statistics are paid centrally by the Dept. of Research policy for all PhD students from Erasmus MC! These are R and the SPSS course. So for Erasmus MC PhD students, these courses are always free, provided you are officially registered as a PhD student.

There is one fee for the entire course. There is no reduction for partial participation.

Some courses have less course days: SPSS 3 days, Survival Analysis 2 days, Management 2 days, Presenting 1,5 days and also other may be shorter as indicated on the website.

Commercial participants, companies & sponsors are invited to inquire about commercial tuition fees and about sponsoring.

All invoices will be sent by email to the mail address that you filled in upon registration. If this address is not correct we use your Erasmus MC address.

Those who register for a course, symposium or workshop agree with these financial conditions.

 

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