In this month’s 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.
Integrative RNA and ChIP-Seq analysis of regulatory T-cells , a Strand NGS application note describes how integrated multi-omics functionality in Strand NGS was used to find the regulatory role of FoxP3 in T-regulatory and T-helper cells. Learn how the gene expression profiles from RNA-Seq and FoxP3 DNA-protein binding sites from ChIP-Seq are integrated. For mor information, please write to us
Using a nasopharyngeal carcinoma case study, this paper highlights the integrated transcriptome analysis capabilities of Strand NGS demonstrating the identification of miRNA – mRNA interactions in regulatory networks.
Read the application note on Integrated mRNA and microRNA transcriptome analysis in Strand NGS by Veena Hedatale and Rohit Gupta. For more information, please contact us
Know about the state-of-the-art algorithms implemented in Strand NGS for detecting the binding sites of transcription factor (narrow peaks) and enriched regions of histone modification (broad peaks) from ChIP-Seq data.
Read the benchmarking study on Calling narrow and broad peaks from ChIP-Seq data in Strand NGS by Rohit Gupta and Anita Sathyanarayanan. For more information, please contact us
Happy to share the release of Strand NGS v2.5. This release comes with many new exciting features and enhancements. Some of the major enhancements include new workflow for MeDIP-Seq analysis, split read alignment, new structural variant caller using split reads, additional RNA QC plots, enhanced RNA-Seq workflow to handle large-scale projects, correlation analysis, meta-data analysis, new and improved CNV visualisations (genome browser and web browser).
Additionally several enhancements are made with respect to visualizations and for high confidence variant calling. All these new features are available once you update the product by clicking on Update Product from the Help menu. For more information, please see the release notes. In case you need any assistance, please write to us at firstname.lastname@example.org or email@example.com
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 live webinar on Copy Number Detection in Inherited Disorders and Somatic Cancer, 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.
Dr. Smita Agrawal, Senior Scientist, Strand Life Sciences, has over 14 years of research experience applying analytical methods to biological problems in the fields of neuroscience, stem cell biology, immunology and genetics. Smita has a PhD in Chemical Engineering from the University of California, Berkeley and has experience working as a post-doctoral scholar in the division of Human Genetics at the University of Minnesota, and as a researcher in the early discovery division of Genentech Inc. At Strand, she heads the clinical data analysis group and also guides the product definition of StrandOmics, Strand’s clinical genomics interpretation and reporting software.
The year 2014 was a great year with exciting features and enhancements updated in Strand NGS. We take this opportunity to thank our clientele and well-wishers for their support and feedback. We wish you all a happy and prosperous new year and look forward to a more fruitful engagement in 2015.
In this blog on Interesting findings by ChIP-Seq and DNA-Seq analysis using Strand NGS, we present two recent publications that analyse ChIP-Seq and DNA-Seq data using Strand NGS.
1. A Comprehensive Profile of ChIP-Seq-Based PU.1/Spi1 Target Genes in Microglia by Satoh et al.
2. Localised Dominant Dystrophic Epidermolysis Bullosa with a Novel de Novo Mutation in COL7A1 Diagnosed by Next-generation sequencing by Nagai et al.
The paper by Satoh et al. investigates the biological role of the transcription factor PU.1 in regulation of microglial functions. Though PU.1 plays vital role in microgliogenesis, the comprehensive profile of PU.1/Spi1 target genes in microglia is unknown. In this paper, Strand NGS was used to analyse SRP036026 ChIP-Seq data set and identify the role of PU.1/ Spi1 in microglial gene regulation. Using Strand NGS, around 5,264 ChIP-Seq-based Spi1 target protein coding genes (Spi1, Irf8, Runx1, Csf1r, Csf1, Il34, Aif1 (Iba1), Cx3cr1, Trem2, and Tyrobp) were identified in BV2 mouse microglial cells. Motif analysis by GADEM revealed the PU-box consensus sequences (5’-GAGGAA-3’) were located on 80.3% of the peaks detected by MACS. By downstream pathway analysis, the ChIP-Seq-based Spi1 target genes were found to show significant relationship with diverse pathways essential for normal function of monocytes/ macrophages (like endocytosis, phagocytosis, lysosomal degradation). Hence PU.1/Spi1 was found to have an important role in microglial gene regulation and any aberrant regulation of these target genes would contribute to neurodegenerative diseases by activated microglia accumulation.
The second paper by Nagai et al. is a case study of a 10-month-old female infant with local Dominant Dystrophic Epidermolysis Bullosa. A targeted next generation sequencing was performed with the proband’s peripheral blood for 16 genes associated with Dystrophic Epidermolysis Bullosa. The sequenced data was aligned and analysed using the DNA variant analysis workflow in Strand NGS (formerly Avadis NGS). A heterozygous single nucleotide variation on chr.3: g.48616827C>T (negative strand) that corresponds to a missense mutation of p.Gly1761Asp in the triple helix domain of COL7A1 was detected. This de novo high confidence mutation was also confirmed by Sanger sequencing. This mutation was detected only in the proband and was not found in the parents, in 100 healthy Japanese alleles as well as in dbSNP.
Webinar on Integrated Biology Solution with Strand NGS and GeneSpring – Case Study on 19 and 20 November
Presented by ‘Agilent Technologies’ and ‘Strand Life Sciences’
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:
• Export of relevant information (reads, region lists, entity lists) from Strand NGS 2.1, for import into GeneSpring 13.0.
• Create an experiment in GeneSpring using the Strand NGS data.
• Perform correlation study and pathway analysis in a multi-omics context.
Dr. Pramila Tata, Director – Applied Science, Strand Life Sciences
Dr. Carolina Livi, Segment Marketing Manager, Agilent Technologies
Session 1 for SAPK/ APFO: November 18, 2014; 8:00 PM PST ( that is 19 November, 9:30 AM IST)
Session 2 for EMEA and India: November 19, 6:00 AM PST (that is 19 November, 7:30 PM IST)
Session 3 for AFO: November 20, 8:00 AM PST (that is 20 November, 9:30 PM IST)
Register on or before November 18, 2014 at http://www.strand-ngs.com/webinar_registration
Dr. Pramila Tata, Director – Applied Science, Strand Life Sciences, has over 15 years experience in cancer research, software support, product development and training technical support teams and field application scientists. Pramila, has earned her Ph.D in Molecular biology from Indian Institute of Science, Bangalore. Prior to joining Strand, she was with Fred Hutchinson Cancer Research Center at Seattle working in cancer biology using budding yeast as a model system. At Strand, Pramila leads the application science team.
Dr. Carolina Livi, Bioinformatics Segment Manager, Agilent Technologies, has over 8 years experience in the field of bioinformatics, regulatory biology and research in cancer and aging. Carolina Livi, has a Ph.D in Molecular developmental biology, from California Institute of Technology. Prior to joining Agilent, Dr Livi has worked with University of Texas Health Science at San Anotonio (UTHSCSA) as a Research Assistant Professor, in the department of Molecular medicine. At Agilent, Dr Livi is Bioinformatics Segment Manager for Life Sciences Research in Academia and Government within the Segment Marketing group.
For more information, please write to firstname.lastname@example.org
Strand is excited to be an exhibitor at the 64th Annual Meeting of the American Society of Human Genetics, San Diego from 18 – 22 October 2014, one of the world’s largest human genetics meetings. At ASHG, Strand will demonstrate the latest version of its state-of-the-art NGS data analysis tool ‘Strand NGS’ and interpretation and reporting platform ‘StrandOmics‘.
At ASHG 2013, Strand had demoed Avadis NGSv1.5 and presented posters on ‘Aneuploidy and Normal Cell Contamination Aware Approach to Detect Copy Number Variations in Cancer Using Next Generation Sequencing Data’ and ‘Shortening the Diagnostic Odyssey: Integrating Genomic, Structural, and Phenotypic Information to Reduce Time of Rare Disease Diagnosis’. This year we are thrilled to present Avadis NGS with its new brand name ‘Strand NGS’ and ‘StrandOmics‘ tool for the first time at ASHG. Loads of new features and utilities with respect to visualizations and interpretations will be highlighted by our representatives at the booth # 338 at ASHG 2014.
This year, we are also presenting four new posters in the sessions on ‘Bioinformatics and Genomic Technology’ and ‘Clinical Genetic Testing’. The posters highlight benchmarking studies we conducted to compare our variant calling and alignment algorithms with some of the other options available to scientists, present case studies from our clinical genetic testing practice in India, and illustrate our variant interpretation and reporting platform, StrandOmics. Detailed information about each of these scientific posters and agenda is mentioned below. For more information visit our ASHG webpage
Come and meet our experts at ASHG 2014, booth #338, to learn more about Strand’s solutions.
To schedule a meeting or demo request of Strand NGS, please write to:
Vinay Paramasivan at email@example.com
About Strand NGS
Strand NGS, an integrated desktop software that enables biomedical researchers to manage, analyze, and visualize data from next-generation sequencing (NGS) experiments. The software is designed to enable biologists to make sense of NGS data by providing a rich, visual environment for QC, analysis, and interpretation of ChIP-Seq, RNA-Seq, small-RNA-Seq, DNA-Seq and Methyl-Seq data. The enterprise version of Strand NGS (server edition) supports multi-member teams to collaborate, share data, and speed up analysis, while the easy backup-restore option allows safe and secure data transfer. For more information visit http://strand-ngs.com/
StrandOmics, is a variant calling and interpretation tool designed to support sequencing lab workflows. The tool reduces variant interpretation and reporting time from days to a few hours. StrandOmics, is based on first-hand experience interpreting variants from hundreds of genomes. To know more visit http://strandomics.com/
Presenter: Dr Veena Hedatale, Senior Application Scientist, Strand Life Sciences
Abstract: Strand NGS (formerly Avadis 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.
Session 1: August 27; Europe +Asia; 11 AM Central European Time (2:30 PM IST)
Session 2: August 27; North + South America; 9 AM Pacific Standard Time (9:30 PM IST)
About presenter: Dr. Veena Hedatale, has a PhD in Plant Genetics from The Radboud University, Netherlands focused on meiosis and recombination. Her prior academic experience at Cornell University was on genetic mapping and gene transformation in Rice. She has worked with Monsanto, and contributed to data mining, database development as well as gene/promoter/pathway discovery for traits related to yield and stress in crop species. At Strand, Veena has worked on Pharmacogenomic analysis of targets and Gene family analysis projects. Currently, she is part of the Strand NGS Application Science team and is involved in the analysis of next generation sequencing data.
For more information, please write to firstname.lastname@example.org