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QIAGEN CLC Genomics Workbench provides tools and workflows for a broad range of bioinformatics applications, including microbiome analysis, isolate characterization through SNP and K-mer trees using NGS data, and antimicrobial resistance characterization. CLC Genomics Workbench is widely used for analyses of bacterial, viral and eukaryotic (fungal) genomes and metagenomes. Topics covered in this webinar include: I. Overview of different tools within MGM application and research areas supportedII. II. Focused review of isolate typing and characterizationIII. a. How to import dataIV. b. Using metadataV. c. Downloading and managing references, including databases of isolates/resistances/MLSTVI. d. Walkthrough of the "Type a Known Species" workflow and review of details for each isolateVII. e. Creating SNP profiles to specific referenceVIII. f. Generate a SNP tree for isolate comparisonIX. g. Export tabular and high-quality graphical outputs in wide range of file formats
QIAGEN OmicSoft Lands allows in-depth investigation of biomarkers through deep curated high quality sample level gene and protein expression data obtained through diverse data sources (GEO, CPTAC, TCGA, GTEx and more). These lands are accessible through Ingenuity Pathway Analysis Explorer feature. In this training the trainer will go over below workflow (designed based on user questions).• Easily locate expression data of interest (pertaining to a disease, treatment, cell type etc.)• Generate expression, correlation and other plots for biomarker investigation and conveniently customize them• For various comparisons (example disease vs normal, response vs no response) perform pathways interpretation through IPA Interpret• Conveniently export or share results
While Ingenuity Pathway Analysis (IPA) accepts wide range of identifiers (gene, transcript, protein, miRNA, metabolite and more) and allows easy mapping/upload of these identifiers, select identifiers require some work before they can be uploaded. In this training, the trainer will use locus tags for a Chinese Hamster Ovary (CHO) cell line dataset as an example to show how such IDs can be made more compatible for optimal mapping in IPA. The trainer will go over strategies such as • Converting such IDs to GenePept IDs to greatly improve mapping• Using Excel's XLOOKUP function to make seamless conversion.• Incorporating metabolomic identifiers using publicly available toolsWhile CHO IDs are used as an example for this training, these strategies can be applied to other IDs as well.
Streamline your research with QIAGEN IPA and access over 200,000 expert-curated analyses from publicly available datasets. This webinar introduces three powerful methods to integrate these datasets with your own research, enhancing discovery and interpretation:• Analysis Match: Automatically find analyses and datasets with comparable or contrasting biological results to validate your findings or uncover unexpected and shared mechanisms• Pattern Search: Match your gene patterns or networks against the Analysis Match collection and find relevant datasets• Activity Plot: Explore the predicted activity of pathways, regulators and more across disease conditions, treatments and moreDon’t miss this opportunity to unlock actionable insights and strengthen your analyses with reliable data and cutting-edge tools.
This webinar will focus on how Human Gene Mutation Database (HGMD) and Ingenuity Pathway Analysis (IPA) can be used together for investigating molecular mechanisms underlying disease pathology. Specifically, the presenter will cover• A brief introduction to HGMD and IPA• Using HGMD to investigate genes and variants of interest• Using IPA for constructing novel networks explaining disease pathology• Easily export tabular and graphical results
Recently we have received some requests from CLC users (as well as CLC RNA-seq certification participants) to go over workflow construction and customization using CLC Genomics Workbench. Accordingly, we are hosting this training. The term workflow refers to bioinformatics secondary analysis pipelines such as DNA-seq, RNA-seq, OTU clustering, de novo assembly and more offered by CLC Genomics Workbench. In this training, the trainer will go over• The basics of workflow construction• How to visualize different steps of the workflow and customize different settings• How to edit workflows (add/remove steps, lock/unlock parameters and more)• How to share workflows• How to install workflows• Other workflow related topics
Are you new to QIAGEN Ingenuity Pathway Analysis (IPA) or interested in expanding your skill set? Join us as we learn more on large dataset analysis and knowledge base queries using QIAGEN IPA.You’ll learn to:• Upload multiple dataset types (e.g., RNA-seq, proteomics, metabolomics) and perform interactive core/pathway analysis in IPA• Learn how to interpret different results, including pathways, key regulators, impact on biological functions/diseases and more• Compare different experimental conditions (e.g., single-cell clusters, disease types) and identify similarities and contrasts• Generate a network for hypothesis generation, even without a dataset or experimental designAlready have an IPA license? Install IPA and start using it now:https://qiagen.showpad.com/share/CBv30blCPKFDUYHRWtAvILearn more about IPA or request a free trial: https://digitalinsights.qiagen.com/ipa
This is a special session put together based on some of the questions we received in recent trainings. IPA allows you to take advantage of deep curate public data from sources such as GEO, GTEx, CPTAC, TCGA and more. This training will focus on below 2 questions mainly but possibly others we receive through the registration and during the live session.1) How to locate pathway analysis of a deep curated public dataset? Example I am interested in 'disease vs normal' or 'treated vs untreated' or 'cell type 1 vs others' comparison from a study. How can I launch pathway analysis of such dataset through IPA project search?2) I also want to investigate such studies and consortia at sample expression level. Example how is a specific gene or protein expressed in disease1 vs disease 2 vs normal tissue or treated vs untreated samples? For 2 genes can we generate a correlation plot?The training may last only ~60min but reserving longer time in case we receive additional questions.
In the absence of genetic testing, is there a clear way forward with diagnosing and treating rare genetic diseases?A great challenge in rare disease research is finding enough affected individuals to create large cohorts. In addition to limited logistical or financial access to NGS, clinicians are often left to rely solely on observed symptoms. Unfortunately, clear guidelines on facilitating diagnoses and care for many diseases in resource-limited settings are non-existent.In this webinar, Claudio de Gusmao, director of the Pediatric Movement Disorders Program at the University of São Paulo, will show how his team developed a diagnostic and management algorithm using KCNA1 mutation-driven episodic ataxia type 1 (EA1) and CACNA1A mutation-driven episodic ataxia type 2 as a model. De Gusmao will explore how:Specific clinical variables can assist in the differential diagnosis of EA1 vs. EA2, such as attack duration, triggers, interictal symptoms, and more.Statistical analyses of published cases can potentially advance rare disease research.Comprehensive, human expert-curated variant data such as from Human Mutation Gene Database (HGMD) Professional can help streamline the process of vetting variants and published studies in preparation for systematic literature reviews.
In this video, we show how to color cells based on the expression of genes of interest in a UMAP. We also demonstrate how to examine expression values from the plot in a selected group of cells. Recent training webinar and tutorial that includes UMAP plot generation from single-cell data: Single-cell RNA-seq, cell hashing and spatial transcriptomicsTutorial: Perform Single-Cell RNA Expression and Velocity Analysis
Here are some quick tips on locating tools in CLC Genomics Workbench version 25+
How to import and visualize spatial transcriptomics data in CLC
How to install the CLC network license manager, network licenses, and CLC Genomics Workbench on Windows
In this video, we demonstrate the different tools that can be launched directly from the UMAP plot with a simple right-click. Recent training webinar and tutorial that includes UMAP plot generation from single-cell data: Single-cell RNA-seq, cell hashing and spatial transcriptomicsTutorial: Perform Single-Cell RNA Expression and Velocity Analysis
Single cell expression matrices can be imported into CLC manually using the import single cell matrix tool or they can be imported automatically using workflows. https://resources.qiagenbioinformatics.com/manuals/clcsinglecellanalysis/current/index.php?manual=Import_Expression_Matrix.html
Direct outputs through a workflow based on sequence count, coverage, and sample quality using branching elements https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Branching_elements.html
Per attendees’ request from a recent training, we are hosting this in-depth training focused on how to effectively construct a network and easily modify it for both no dataset or dataset (RNA-seq, proteomics, etc.) in QIAGEN Ingenuity Pathway Analysis. In this interactive training, attendees will learn:• How to construct a network from scratch or open a network/pathway of interest from their own analysis or Ingenuity database• How to effectively use tools present in build and overlay menu to add molecules (genes/proteins), chemicals, metabolites, biological processes/diseases and more of their interest • How to modify the network (ex. keep only specific type of relationship like activation, phosphorylation, protein-protein binding and more)• Perform in silico prediction (ex. if a drug, siRNA or CRISPR were to reduce activity of a gene/protein, how will impact remaining genes/proteins/diseases on that network)• Export high resolution graphics or tabular relationships and/or make the created network usable in future pathway analysis Additional QIAGEN Digital Insights (QDI) scientists will be on the call to answer your questions and help with other inquiries such as how to install the software.
QIAGEN’s CLC bioinformatics software portfolio provides user-friendly and intuitive solutions that run on any platform. This helps scientists to focus on the biology of their research without requiring them to write code, or compile and run software from the command line.At QIAGEN we understand, however, that no single piece of software can meet the needs of every bioinformatics challenge. Sometimes, you need to supplement standard pipelines with your own scripts, open-source tools or third party applications from the command-line.Accordingly, this training will go over:• A quick introduction to CLC Genomics Workbench• Wrapping an external application into the CLC environment• Running external application alongside CLC tools and exporting results.
In this on-demand recording from ACMG 2024, hear from Dr. David Bick, Principal Clinician of the Newborn Genomes Program at Genomics England, as he discusses the first-of-its-kind initiative aiming to sequence the genomes of 100,000 newborns in England to screen for over 200 selected conditions. In his talk, you will learn about: The development and deployment of The Generation StudyHow Genomics England selected the genes and conditions to include in the point-of-care testHow QIAGEN provided expert-curated content for 69,844 pathogenic or likely pathogenic variants across all 209 conditionsThe variant prioritization strategy used by Genomics England to enable efficient and actionable reportingThe anticipated research outcomes and future plans Learn more about how QIAGEN is supporting The Generation Study here.
For RNA-seq data, you will learn how to:• Import FASTQ files, cell matrix files and metadata and how to download references• Map reads to a reference genome and generate gene and transcript counts and QC reports displaying % mapped reads, knee plots, etc.• Generate visualizations of results, such as heatmaps, differential expression tables, PCA/PCOA plots, Venn diagrams, sankey plot and others• Easily customize RNA-seq workflows • Export publication-quality graphics, tables and reports Per audience request• Send differential expression tables to QIAGEN Ingenuity Pathway Analysis directly from QIAGEN CLC Genomics Workbench to analyze and interpret relevant pathways
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