Whole genome sequencing (WGS) provides unprecedented access to genomic information, expediting breakthroughs in human healthcare, oncology, biomarker discovery, agriculture, and metagenomics.
GENEWIZ Whole Genome Sequencing Services from Azenta Life Sciences utilize the latest technologies and bioinformatics to deliver high-quality data and comprehensive analysis for the genomes of all organisms, including humans, animals, plants, bacteria, and viruses.
Whole genome sequencing (WGS) is the comprehensive read and analysis of an entire genome, including non-coding regions of the genome.
WGS is used to facilitate discovery of novel genes and gene variants associated with disease. In the case of human WGS, researchers use WGS to explore gene expression and functional elements of the genome that help predict an individual’s response to drug therapies. WGS is also used to study the evolution of infectious pathogens and mechanisms of disease-causing mutation. Find the right NGS solution for your project using our interactive guide.
For those new to bioinformatics, analyzing massive amounts of NGS data can be a daunting task. Download Azenta’s bioinformatics quick start guide to learn how to analyze whole genome sequencing (WGS) and RNA sequencing (RNA-Seq) data with bioinformatics tools to reveal biological insights for your research.
In this PacBio-hosted webinar, Jonas Korlach, PacBio Chief Scientific Officer, and Dave Corney, Azenta Associate Principal Scientist, Next Generation Sequencing, describe the recent release of Sequel System 6.0, which has revolutionized long-read sequencing by providing users the ability to generate highly accurate single-molecule reads.
High-quality high molecular weight (HMW) genomic DNA (≥50 kb) is critical to achieving long read lengths on platforms such as the 10x Genomics® Chromium™ and the PacBio Sequel. Follow these guidelines to generate the best possible WGS results.
In this webinar originally presented at the ASHG 2020 Virtual Meeting, learn how low-pass WGS overcomes the inherent limitations and biases of traditional arrays, offering an inexpensive, high-throughput alternative for detecting genome-wide genetic variation and novel variants.
In this recording of our WGS bioinformatics workshop & roundtable discussion led by bioinformatics scientist Zain Alvi, Ph.D., we'll guide you through the WGS bioinformatics process to help you learn to interpret WGS bioinformatics results, as well as address common challenges and answer frequently asked questions (FAQs).