These trainings are offered by Qiagen, not BTEP, and are listed here for your convenience. (Last updated Feb. 1st)
To access Qiagen IPA and Land Explorer, NCI CCR researchers can request installation by service.cancer.gov
Feb. 2nd, @ 1PM, New user training: Large dataset analysis and knowledge base queries using QIAGEN Ingenuity Pathway Analysis (IPA)
Join us for a 90-minute training session for new users of QIAGEN IPA.
In this training, you’ll learn how to:
. Upload your dataset (RNA-seq, scRNA-seq, proteomics, metabolomics and more) and perform interactive core/pathway analysis in IPA
. Understand the different result types produced (pathways, key regulators, impact on biological functions/diseases and more)
. Compare different experimental conditions (treatments, time points, single-cell clusters, disease types and more) and identify similarities and contrasts
. Generate a network even without a dataset or experimental design for hypothesis generation
Feb. 9th, @ 1PM, Metatranscriptome analysis, annotation and pathways investigations using QIAGEN CLC Genomics Workbench
Using QIAGEN CLC Genomics Workbench, we will go through a pipeline for analyzing metatranscriptome NGS data from microbial communities and use the data to perform pathway interpretation. You’ll learn how to:
· Import “raw” NGS sequencing data and prepare the samples for analysis
· Find relevant annotated genomes with a curated reference database while removing ribosomal RNA with the SILVA database (database of rRNAs)
· De novo assemble the unclassified reads into contigs to also find transcripts of taxa not present in the reference database
· Map the reads to the assembled contigs and database
· Build a functional profile of the samples to get an abundance of GO terms.
· Perform statistical analysis of the groups
· Apply pathway analysis on the differential abundance analysis using MetaCyc database
Feb. 14th, @ 1PM, Single-cell RNA-seq data analysis and interpretation
In this training, you’ll will learn how to analyze and interpret your own scRNA-seq data using QIAGEN CLC Genomics Workbench and QIAGEN Ingenuity Pathway Analysis (IPA).
In this 90-minute training, you’ll learn how to:
. Start with FASTQ, cell matrix file and/or differential expression file for scRNA-seq data
. Depending on your preference, either automate or customize your analysis pipeline/workflow
. Easily generate visualizations such as t-SNE, UMAP, heatmap, differential expression table, dot plots and more
. Upload differential expression data to QIAGEN IPA (either from CLC or from another source)
. Perform pathway analysis on scRNA-seq data and compare different clusters to discover novel biological mechanisms, cell type-specific biomarkers and key regulators/targets
. Export results in the form of high-quality images or tabular format
Feb. 21st, @ 1PM, IPA Deeper Dive: Making most out of user’s core analysis and new features
Many of you who use QIAGEN Ingenuity Pathway Analysis (IPA) have requested a deeper dive into the IPA core analysis (also known as expression analysis – performed on RNA-seq, scRNA-seq, proteomics and many other ‘omics data). You’ve specifically requested to cover topics like causal networks, regulator effects, etc., in more detail.
That’s why we’ve designed this training to focus on thesetopics and more:
· What are the different result types produced by an IPA core analysis?
· What are the differences between causal network vs. mechanistic network vs. regulator effects?
· How do you predict molecular activity in IPA? What is a Z-score?
· What is the new bubble plot feature?
· How can I edit, expand and modify the network the way I want it? For example, add a disease or gene(s) of interest, remove certain connections, etc.
Feb. 28th, @ 1PM, IPA deeper dive: miRNA investigation using QIAGEN Ingenuity Pathway Analysis (IPA)
In this 90-minute training session, you will learn how to identify target mRNAs for your miRNAs of interest and associate them with pathways, diseases, biological functions, tissues and cell types.
. How to analyze miRNA-seq datasets alone, or both miRNA and corresponding mRNA datasets together
. How to use QIAGEN IPA without a dataset, using miRNA IDs
. Introduction to databases and curated content specific to miRNA
. How to effectively apply various filters and functionalities to identify biomarkers, key targets and novel biological mechanisms.