Webinars Archive | Strand NGS

Webinars Archive

This is an archive of our previous webinars. If you are interested in attending a live webinar, visit our webinar registration page for a listing of upcoming sessions. If you have any questions on the topics below, feel free to contact us and we will be happy to schedule a Q&A session for you.

Transcriptome Analysis to Investigate Hox Gene Functions
Watch this video to know about transcriptome analysis of a developmental biology data set. This webinar highlights the use of Strand NGS 3.0 features such as sample correlation, clustering, PCA, Venn diagrams, plotting list associated values, and elastic genome browser for bioinformatics-based confirmation of histological findings.

ChIP-Seq Analysis of Fibroblasts Under Oxidative Stress
Watch this video to know about the alignment and analysis of a ChIP-Seq data set in Strand NGS 3.0. Dealing with oxidative stress, this webinar illustrates the use of features such as TSS plots, peak detection and annotation, motif detection and motif scan in understanding interesting biological phenomena.

Integration of NGS and Machine Learning for prediction of post-operative recovery, by Dr Mario Deng, UCLA
Strand NGS supports a comprehensive and flexible RNA-Seq data analysis workflow consisting of Alignment, Quality Assessment, Filters, and a range of analysis and visualization options that help in studying a variety of samples and answering important biological questions.In this webinar, Dr. Deng will discuss the analysis of transcriptome, flow cytometry and cytokine data from pre-operative blood samples of advanced heart failure patients undergoing Mechanical Circulatory Support (MCS) surgery. He will discuss in detail the identification of prominent clinical variables, a set of transcriptome biomarkers, and their role in the context of systems biology. Finally, the application of Class Prediction algorithms in Strand NGS for identification of high-risk patients will be illustrated. This immunobiology based study highlights the potential of machine learning techniques in clinical risk prediction and patient management, and from a clinician’ s perspective, the utility of biomarker discovery studies in helping patients make more informed decisions as a step towards personalized precision medicine.

Strand NGS Server: or, why clinical bioinformaticians love Strand - Joint webinar with Labroots
Learn about Strand NGS server version, which is geared towards small-to-medium scale clinical labs with high-volume sequencing throughputs and low turnaround times. The talk is in three parts. The first part describes how Strand NGS Server marshals the various computational resources available to a typical clinical lab. It also discusses the primary advantage of Strand NGS Server over its desktop counterpart: namely, collaboration. The second part describes the ease of setting up a given pipeline in Strand NGS server, and speaks of four examples, each corresponding to a different clinical panel: germline, somatic, clinical exome and rare diseases. The last part describes a day in the life of a bioinformatician, and goes over a few typical use cases of Strand NGS Server.

Webinar on fast and accurate variant calling in Strand NGS v3.0
Continuing our webinar series, we'll present Strand NGS v3.0 best-practices: a workflow that identifies highly accurate variants from raw reads. Our best practices workflow is twice as fast as its GATK counterpart, and results in precision/recall rates of up to 99%/98% on whole exome and whole genome samples. We'll also speak briefly about some of the other features in v3.0 including one-shot pipelines, TSS plots, RNA-Seq performance improvements, and, for the first time, HGVS notations for SNP effect analysis.

Webinar on DNA-Seq data analysis
Strand NGS – supports analysis of whole exome, whole genome and targeted sequencing experiments. The DNA-Seq workflow includes the ability to detect variants (SNPs, MNPs and short InDels), annotate them with dbSNP, and report for each SNP the kind of effect it has on the genes and provides list of affected genes. Biological contextualization of the affected genes can be performed by downstream analysis such as GO, GSA, pathway analysis. Large structural variations, including large insertions, deletions, inversions, and translocations, can also be detected with paired-end and mate-paired data. Copy number variation (CNV) analysis can be done using tumor-normal pairs. Strand NGS has easy to use built in pipelines (with an option to customize) for time consuming jobs which automates analysis and leaves more time for end data interpretation. In this webinar we will discuss case studies using the DNA-Seq data analysis workflow in Strand NGS and also highlight on parameters within each feature that can be optimized depending on datasets and analysis needs.

Webinar on RNA-Seq data analysis
Strand NGS supports an extensive workflow for the analysis and visualization of RNA-Seq data. The workflow includes Transcriptome/ Genome alignment, Differential expression analysis with Statistical approach and Splicing events detection. Strand NGS also supports novel discovery like identification of novel genes, exons and novel splice junctions, alongside it can also detect gene fusion events. Further downstream analysis such as GO and pathway analysis can be performed on the set of interesting genes. The product has an option to create pipelines for time consuming jobs which automates analysis and leaves more time for end data interpretation. This webinar will give an overview of the features in the RNA-Seq data analysis workflow in Strand NGS and also highlight on parameters within each feature that can be optimized depending on datasets and analysis needs.

Implications of Next Generation Sequencing in Molecular Diagnosis of Cancer- Case studies
Genetic testing requires screening of the entire gene, which by conventional sequencing is time consuming and expensive. Next Generation Sequencing (NGS) based approaches increase the sensitivity of mutation detection, making it fast and cost-effective compared to the conventional tests performed in a reflex-testing mode. Strand NGS includes workflows with quality assessment and filter sections that do not require any manual intervention. Post-analytical workflows in Strand NGS allow users to execute sequence analysis with stringent filtering to eliminate false positive and low quality reads. This simplifies the analysis in large scale cohort settings, where every sample needs to be processed identically. In this webinar we will discuss the implications of next generation sequencing based tests in multi-gene testing. We will also show how NGS based tests help to identify copy number variations, split read analysis and breakpoint identification. Finally, we will show a brief glimpse of Indian cohort data, where NGS based tests have shown improved mutation detection. In this webinar, we will present clinical case studies in on Hereditary Breast and Ovarian Cancer (HBOC) and Retinoblastoma patients to demonstrate how CNV analysis in Strand NGS enables researchers to detect and visualize copy number changes ranging from single exon to full gene.

Streamlining large scale analysis using the Strand NGS Pipeline Manager
Strand NGS includes comprehensive workflows for DNA-Seq, RNA-Seq, Small RNA-Seq, ChIP-Seq, MeDIP-Seq, and Methyl-Seq analysis. Each workflow includes a quality assessment and filter section, followed by a workflow-specific analysis section. The pipeline functionality in Strand NGS allows users to execute a sequence of analysis steps with specific parameters - all without any manual intervention. This simplifies the analysis in large scale sequencing projects where every sample needs to be processed identically.
In this webinar we will discuss the pre-packaged pipelines present in Strand NGS. The packaged pipelines have well-chosen default parameters and are suitable for users analyzing data for the first time in the tool. We will also show how advanced users can customize pipelines and share them with other Strand NGS users. Finally, we will show a brief glimpse of an elaborate pipeline that aligns reads, filters poor-quality matches, computes coverage metrics, identifies variants, checks for sample cross-contamination, and emails quality reports - all from within Strand NGS.

Detection of Structural Variants in Targeted Sequencing
Chromatin immunoprecipitation (ChIP) followed by high throughput sequencing (ChIP-Seq) is one of the widely used approaches for elucidating interactions between DNA and proteins. It is an essential tool for researchers to understand the role of transcription factors or histone modifications in gene regulation. While for most TFs, enriched regions typically form sharp peaks covering short regions of DNA, the pattern of reads for many types of histone modifications span regions of upto several hundred kilobases. In this webinar, we will demonstrate and assess the algorithms in StrandNGS for both narrow and broad peak calling. Specifically, results from using 'MACS' algorithm for detecting the FOXA1 transcription factor binding sites and from 'Find Enriched Regions' approach for detecting histone H3K36 modification regions will be discussed.

Calling narrow and broad peaks from ChIP-Seq data
Structural Variants (SVs) have long been implicated in many human diseases such as cancer, making their detection important in clinical genomics. Strand NGS 2.5 includes a new workflow step for detecting these variants based on split reads that span the breakpoints corresponding to the variants. Detection of SVs using split reads provides breakpoints with a higher precision compared to the methods based on paired-end reads. In this webinar, we will describe this method and demonstrate its application to detection of somatic gene fusions in targeted sequencing data. We will also show how the detected SVs can be visually validated in the elastic genome browser of Strand NGS.

Copy Number Detection in Inherited Disorders and Somatic Cancer
Copy number variants constitute a significant fraction of genomic alterations responsible for cancer and various inherited disorders. In a clinical setting, performing focused NGS testing based on a panel of relevant genes is both economical and provides faster results. Thus the ability to detect CNVs from gene panel based NGS tests increases the diagnostic yield significantly. In this webinar, we will present few clinical case studies to demonstrate the new CNV analysis workflow in Strand NGS that enables researchers to detect and visualize copy number changes ranging from single exon to chromosome level events.

An integrated RNA and DNA approach to unravel genetic regulation in cancer
Whole exome DNA sequencing (WES) or whole genome DNA sequencing (WGS) allows detection of mutations and polymorphisms in all exonic and genomic regions, respectively, while messenger RNA sequencing (RNA-Seq) enables quantitative analysis of gene expression. Mutations in the genome result in diverse transcriptional aberrations that can be missed in a stand-alone WES/WGS analysis. An integration of DNA variant analysis and RNA-Seq analysis enables one to investigate the consequences of genomic changes in the RNA transcripts including germline and somatic changes, imprinting, RNA editing and allele specific expression (ASE). In this webinar, we will demonstrate this integrated approach using Strand NGS to identify high confidence mutations, RNA editing events and ASE in cancer.

Integrative RNA and ChIP-Seq analysis of regulatory T-cells
Analyzing RNA-Seq data gives us the gene expression profiles and variations across conditions. The ChIP-Seq data analysis provides information on where a particular protein might bind in the genome and which genes it regulates under a particular condition. Combining these two studies might help us answer what effect a transcription factor binding might have on gene expression. Here we show a case study in which we demonstrate how such an integrative analysis helps in investigating the role of transcription factor FOXP3 on gene expression in regulatory T-cells.

Integrated Multi-Omics Analysis with Strand NGS and Agilent Technologies GeneSpring® 13.0 - Case Study and Demo
Integrating Next Generation Sequencing data with other omics- studies is now possible with release of GeneSpring® 13 and Strand NGS 2.1, opening up newer avenues for analysis and interpretation of NGS experiments. In this webinar, we will demonstrate the new integrated analysis workflow using high throughput microarray and next generation sequencing data. Using a case study the following functionality of the multi-omics approach would be highlighted- i) Export of relevant information (reads, region lists, entity lists) from Strand NGS 2.1, for import into GeneSpring® 13.0. ii) Create an experiment in GeneSpring® using the Strand NGS data. iii) Perform correlation study and pathway analysis in a multi-omics context.

Integrated pathway analysis in Strand NGS
Strand NGS supports functional analysis of entities from diverse experiment types to understand their role in a biological process. This webinar will illustrate various ways of integrating next generation sequencing data from different experiments. With focus on visualization of biological data, analysis steps showing the use of an entity list to find statistically significant pathways will be discussed. The pathways can either be derived from literature (like NLP, MeSH) or curated pathways (like Wikipathways or BioCyc). The webinar will also provide more insights into how one can overlay data from single or multiple sequencing experiments onto the same pathways simultaneously.

Methyl-Seq data analysis in Strand NGS- formerly Avadis NGS
Strand NGS (formerly Avadis NGS) supports an extensive workflow for the analysis and visualisation of Methyl-Seq data – such as from whole genome or targeted experiments. In this webinar, we'll cover the workflow features for detection and quantification of methylation levels in individual samples, detection of differentially methylated cytosines across samples/target regions, intra-sample analysis, and assessing methylation effects at the genic level. Further downstream analysis such as GO, pathway analysis on the set of affected genes will be covered briefly.

Discovery and characterization of miRNAs expressed in cancers
miRNAs constitute a family of small RNA species that function as important regulators of cellular processes by modulating gene expression. In this webinar, we will focus on miRNA analysis using next generation sequencing cancer data with insights to alignment, quality checks, filtering and analysis steps. Using the small RNA workflow in Strand NGS, users can rapidly and easily characterize miRNA expression and function by expression profiling, identification of sequence isoforms, prediction of novel miRNAs, and prediction of potential mRNA target molecules Watch

Configuring SNP detection pipelines for accurate analysis of clinical samples
Running a SNP detection pipeline and identifying high quality variant calls quickly is challenging. This is especially true in the case of clinical labs where multiple panels are used and kit-specific biases can result in false positive SNP predictions. In this webinar, we show how one can use the powerful visualization features of Strand NGS to quickly detect false positive SNP predictions, identify the cause of the errors, and fine-tune the detection pipeline for accurate analysis. Watch

RNA Seq Data Analysis in Strand NGS
StrandNGS supports an extensive workflow for the analysis and visualization of RNA-Seq data. The workflow includes alignment, standard differential expression analysis and differential splicing analysis. Strand NGS supports novel discovery like identification of novel genes, exons and splice junctions. It also detects transcriptome variants and gene fusion events. Further downstream analysis such as GO and pathway analysis can be performed on the set of interesting genes. The product has an option to create pipelines for time consuming jobs which automates analysis and leaves more time for end data interpretation. This webinar will give an overview of the features in the RNA-Seq data analysis workflow in Strand NGS and also highlights on parameters within each feature that can be optimized depending on datasets and analysis needs. Watch

Detecting Copy Number Variations in Cancer using Next Generation Sequencing Data
Recent growth in next generation sequencing (NGS) data has enabled us to detect copy number variations (CNV) at an unprecedented resolution. However with several technical and biological challenges such as noise and GC bias in the data, aneuploidy of cancer cells, contamination of the tumor sample by normal and stromal cells, and tumor heterogeneity amongst others, the task of CNV detection remains non-trivial. In this webinar, we will present some of the recent work in this direction and describe our approach to detecting CNV regions in the cancer genome with respect to the normal genome. We will also discuss how sample-specific biological parameters like average ploidy and normal cell contamination can be estimated using NGS data. Finally, we will show how this enables us to more accurately identify the CNV regions across the genome and also assign absolute copy numbers to them. Watch

Local Realignment and Base Quality Score Recalibration
Strand NGS is our solution to the analysis of next generation sequencing data and features comprehensive support for end-to-end DNA-Seq analysis. The DNA-Seq workflow includes algorithms and general purpose tools for detecting and predicting the effects of SNPs and InDels, as well as for finding larger structural variations. The workflow in our upcoming release will be extended to include support for (i) base quality score recalibration to account for inaccuracies and biases in base quality scores reported by sequencers, and (ii) local realignment to handle multiple mismatches in alignment near InDels. In this webinar, we will describe our approach for base quality score recalibration and local realignment and demonstrate how these steps can help to decrease false positive variant calls in the downstream analysis.

RNA-Seq Alignment in Strand NGS
The next version of Strand NGS features enhancements to the RNA-Seq analysis workflow, namely an extension of the COBWeb alignment algorithm to enable alignment of RNA-Seq reads. Reads obtained from single/paired-end libraries or directional RNA-Seq protocols can be imported into the new RNA-Seq Alignment experiment. This workflow allows users to perform alignment against a transcript model and additionally against the genome.

Find Significant SNPs using Strand NGS
SNP verification and prioritization is one of the most time consuming tasks in variant analysis. Strand NGS 1.3 includes numerous changes to make end-to-end SNP analysis easy and intuitive. The SNP detection algorithm has been enhanced to improve accuracy. In this webinar, we will show you the new "Find Significant SNPs" analysis workflow in Strand NGS 1.3. This workflow supports multiple experimental setups and can be used to quickly identify population-specific variants, somatic mutations, and tumor-specific markers via an intuitive graphical user interface.

Analysis of Ion Torrent Data in Strand NGS
The Strand NGS includes a new aligner - COBWeb - that is fully capable of aligning the long, variable-length reads generated by Ion Torrent sequencers. In this webinar, we will show the pre-alignment QC plots and illustrate how they can be used to set appropriate alignment parameters for aligning Ion Torrent reads. For users who choose to import the BAM format files generated by the Ion Torrent Server, we will describe the steps needed for importing amplicon sequencing data into Strand NGS. Users of the Ion AmpliSeq™ Cancer Panel will learn how to easily import the targeted mutation list and verify the genotype call at the mutation sites. We will illustrate how to use the Find Significant SNPs feature to quickly identify high-confidence SNPs present in a majority of the samples, rare variants etc.

Support for MiSeq Data in Strand NGS
Strand NGS 1.3 provides special support for analyzing data generated by MiSeq™ sequencers. In this webinar, we will describe how the data in a MiSeq generated "run folder" is automatically loaded into the Strand NGS software during small RNA alignment and DNA variant analysis. This is especially helpful in processing the large number of files generated when the TruSeq™ Amplicon Kits are used. We will describe how to use the QC steps of Strand NGS to check if the amplicons have sufficient coverage in all the samples. Regions with unexpected coverages can easily be identified using the new region list clustering feature. We will illustrate how to use the Find Significant SNPs feature to quickly identify high-confidence SNPs present in a majority of the samples, rare variants etc.

Alignment of raw reads in Strand NGS 1.3 using COBWeb
The upcoming release of Strand NGS 1.3 provides support for aligning raw reads for small RNA, ChIP-Seq and DNA-Seq analysis. The alignment algorithm integrated with Strand NGS is a new proprietary algorithm based on the Burrows Wheeler Transform. We have christened our new algorithm COBWeb - a metaphor for strength in simplicity as well as a reflection of multi-scale design, the attributes that have inspired the algorithm. COBWeb is optimized to handle both short and long reads and is capable of handling an arbitrary number of gaps and mismatches, so you won’t need to search for other aligners, which are often limited to either a specific class of reads or alignment characteristics.

Small RNA Analysis in Strand NGS 1.3
Strand NGS already has comprehensive analysis pipelines for RNA-Seq, DNA-Seq and ChIP-Seq data. The next version of Strand NGS comes with a new pipeline for the analysis of small RNA data as a separate experiment type. Watch the recording of this webinar, to know more about what’s new in Strand NGS 1.3. In this webinar, we will describe the new small RNA read aligner, small RNA specific QC and filtering steps, quantification, and differential expression method. Since annotations for small RNA species are usually incomplete, we will show you how to detect and classify novel small RNAs. In addition, we will also show you how to use the multiple miRNA target prediction databases to identify target genes on which downstream analysis can be performed.

Analyzing Whole Genome Experiments
This webinar focuses on the scalability and performance of Strand NGS when importing and analyzing large data sets. It includes details on identifying and analyzing SNPs and SVs and their effects on the transcript. We will be using a Yoruba high coverage whole genome sample for this demonstration.

Quality Control in Strand NGS
Watch the recording of this webinar if you would like to find out more about quality control of NGS data and the QC features on offer in Strand NGS. The webinar helps you understand how you can perform various Quality Control (QC) steps in Strand NGS to make sure you retain only the best reads for the later analysis steps. It covers the various QC visualizations available in Strand NGS that allow you to efficiently determine how good (or bad) the reads in your data are. Following that, we demonstrate how to use the available QC filtering steps to remove bad quality reads.

Pathway Analysis in Strand NGS
Many NGS analyses like differential expression, peak finding, and SNP effect analysis, result in a list of genes. Strand NGS provides several downstream tools like GO analysis, GSEA, and pathway analysis for further exploration of these entity lists. This webinar is focused on the pathway analysis features in Strand NGS. We will briefly describe the packaged interaction databases that contain ~2 million interactions derived using Strand's proprietary Natural Language Processing (NLP) algorithms on 16 million Medline abstracts.
Watch the recording of this webinar to learn how to effectively query the interaction databases to detect relationships between entities of interest, how to create pathways from the interaction database, how to import curated pathways from external sources such as Reactome and Cancer Cell Map, and how to use the saved pathways in data interpretation.

Analyzing Cancer Data with Strand NGS
This webinar focuses on the analysis of NGS data in the context of cancer biology using the various analysis and biological interpretation tools available in the RNA-Seq and DNA-Seq workflows of Strand NGS. We will discuss differential gene expression, alternate transcript isoforms, somatic and germline SNPs, and aneuploidies, which are all commonly studied in various forms of cancer.

Genome Browser Highlights
Did you know that Strand NGS has an embedded, feature-rich Genome Browser? This webinar will show you how to the best use of all its features, as well as how to customize it for better interaction with your data and improved visualization of your analysis results to use in publications.

ChIP-Seq Webinar
This webinar will focus only on the ChIP-Seq workflow of Strand NGS. We will explain the various peak finding algorithms available in Strand NGS and the GADEM motif discovery algorithm. In addition, the webinar will also cover the downstream analysis options available in Strand NGS, including gene ontology analysis and pathway analysis.

DNA-Seq Webinar
This webinar will focus only on the DNA-Seq workflow of Strand NGS. Register for this webinar if you are interested in learning more about detecting and predicting the effects of SNPs and InDels, as well as finding larger structural variations and translocations.

RNA-Seq Webinar
This webinar will focus only on the RNA-Seq workflow of Strand NGS. It covers the main steps of analyzing RNA-Seq data, including gene expression analysis, transcript expression analysis, SNP detection, and how to discover novel genes and novel splice junctions using Strand NGS.

Introductory Webinar
This webinar is for everyone who is interested in learning the basics of sequence data management and how to start analyzing sequence data, using the workflows for the three most common NGS experiment types: ChIP-Seq, RNA-Seq, and DNA-Seq. It also covers pathway analysis and data exploration in the highly-interactive genome browser in Strand NGS.