Get to know IPA

Author:

QIAGEN Digital Insights

Get to know IPA

IPA Webinar: Part 1: Introduction to Ingenuity Pathway Analysis

Learn how to quickly and easily identify significant pathways, discover potential novel regulatory networks, and get the most out of your ‘omics data!

IPA has broadly been adopted by the life science research
community and is cited in thousands of articles for the analysis, integration,
and interpretation of data derived from ‘omics experiments, such as RNA-seq,
small RNA-seq, microarrays including miRNA and SNP, metabolomics, proteomics,
and small scale experiments. Hosted by two QIAGEN Senior Scientists, this
series will show you step-by-step how to implement and use IPA to get the most
out of your data.

Part 1: Introduction to the IPA Core Analysis

Learn how to view and interpret Core Analysis results in IPA,
which allows you to relate the molecules in your dataset to information in the
QIAGEN Knowledge Base. You will learn how to:

  • Uncover
    signaling and metabolic canonical pathways enriched in your data
  • Predict
    activation or inhibition of upstream regulators
  • Identify
    biological functions and diseases that are predicted to be increasing or
    decreasing
  • Generate
    causal hypotheses
  • Build
    networks describing potential molecular interactions of your dataset
    molecules
  • Compare
    your analyses to thousands of analyses created from public datasets

 

IPA Webinar: Part 2: Formatting and Uploading Your Dataset into IPA
IPA has broadly been adopted by the life science research community and is cited in thousands of articles for the analysis, integration, and interpretation of data derived from ‘omics experiments, such as RNA-seq, small RNA-seq, microarrays including miRNA and SNP, metabolomics, proteomics, and small scale experiments. Hosted by two QIAGEN Senior Scientists, this series will show you step-by-step how to implement and use IPA to get the most out of your data.

Part 2: Formatting and Uploading Your Dataset into IPA

Learn how to format your own data and upload it into IPA so that you can perform pathway visualization and various different types of analyses. Learn how to:
• Format and upload the data to be analyzed by IPA
• Explore your uploaded data and start an analysis

IPA Webinar: Part 3: Search and Explore in IPA
IPA has broadly been adopted by the life science research community and is cited in thousands of articles for the analysis, integration, and interpretation of data derived from ‘omics experiments, such as RNA-seq, small RNA-seq, microarrays including miRNA and SNP, metabolomics, proteomics, and small scale experiments. Hosted by two QIAGEN Senior Scientists, this series will show you step-by-step how to implement and use IPA to get the most out of your data.

Part 3: Search and Explore in IPA

Learn how IPA’s knowledge and discovery tools can accelerate your research with the use of recent literature findings and assistance in hypothesis generation. This webinar will describe how to explore inter-related information about genes, biological pathways and more using interactive and customized tools. Leverage this information instantly without needing to upload your data.

IPA Tips and Tricks
In this talk, Lynne Mullen, Ph.D. Senior Scientist, QIAGEN Digital Insights presents a series of helpful tips and tricks in QIAGEN IPA. Geared for all levels from beginning to advanced users, Dr. Mullen walk the audience through:
• Application Preferecnes
• Data Upload
• Creating Core Analyses
• My Pathway Tools
• Additional resources for IPA

 

Data Formatting in IPA
Learn how to format your dataset for upload and subsequent analysis in IPA. In this video tutorial, you will discover the best practices for structuring your dataset and the data measurement value types you can use for various IPA analyses.

 

Data Upload in IPA
Learn how to upload your dataset into IPA. In this video tutorial, you will discover the best practices for mapping the molecular identifiers and observation information that are present in your dataset. You will also learn how to annotate your dataset with metadata.