VIENNA, AUSTRIA, AND RIJSWIJK, THE NETHERLANDS, June 12, 2018 – Lexogen, a transcriptomics and next-generation sequencing company and BlueBee, a global bioinformatics platform, have announced today the implementation of QuantSeq Unique Molecular Identifiers (UMI) data analysis pipeline on the BlueBee genomics analysis platform. This collaboration offers QuantSeq users utilizing UMIs the opportunity to analyze samples in a convenient and rapid manner without the need for prior bioinformatics experience.
QuantSeq is a 3’ mRNA-Seq library prep protocol, which is the method of choice for RNA-Seq gene expression analysis due to the simplicity, cost effectiveness, and data quality offered by this technology. The QuantSeq protocol has been recently complemented with the launch of dual indexing barcodes (total 192 unique barcodes) and UMIs. Dual indexing helps detect and identify index hopping, which is an issue recently reported for sequencing instruments with patterned flow cells. Dual indexing barcodes also help avoid cross-contamination and minimize index mis assignment. UMIs are used to eliminate possible PCR duplicates in sequencing datasets and therefore facilitate unbiased gene expression profiling. The basic principle behind the UMI deduplication step is to collapse reads with identical mapping coordinates and UMI sequences. This step helps increase the accuracy of sequencing read counts for downstream analysis of gene expression levels.
The analysis and interpretation of QuantSeq data with UMIs requires specialized bioinformatics tools. Lexogen has implemented the QuantSeq-UMI data analysis pipeline on the BlueBee platform, providing kit users with a simple, streamlined tool for data analysis through actionable report and data management. Similarly to the previously integrated QuantSeq data analysis pipeline, access to the UMI data analysis will be offered with a complimentary software activation code included in each QuantSeq-UMI kit. The integration of BlueBee data analysis automation in the Quantseq pipeline promises faster, more convenient, and centralized data analysis for all users.
This is in continued efforts by the strategic partners, Lexogen and BlueBee, to streamline and expedite genomic data analysis and implementation. BlueBee driven data analysis automation has already been successfully integrated into Lexogen’s Quantseq and SLAMseq kits, where SLAMseq is a new approach for analyzing time-resolved gene expression (published in Nature Methods and Science) using QuantSeq library generation.
“We are delighted to progress our relationship with BlueBee in providing our next integrated data analysis pipeline, including tools to measure PCR bias revealed by the addition of UMIs as part of the QuantSeq product family. All QuantSeq data analysis pipelines are transparent, streamlined, optimized for the particular protocol and run on a secure platform. We expect similarly integrated data analyses to expand to other Lexogen kit families,” stated Dalia Daujotyte, Head of Business Development at Lexogen.
Lexogen is a transcriptomics and next-generation sequencing company, focusing on the development of technologies for complete transcriptome sequencing. Their portfolio includes innovative molecular biology kits, software, and services for RNA- Seq.
To learn more, visit www.lexogen.com and follow @lexogen.
BlueBee offers a secure global bioinformatics platform to process, analyze, share, and store genomics data. Through a private cloud service, BlueBee supports users in clinical diagnostics, therapeutics, and research with advanced analytics for genomic data driven medicine. BlueBee offers its partners – diagnostic and translational research assay kit providers, fit-for-purpose data solutions that accelerate end-to-end assay completion and offer a seamless user experience, adding value for both the end user and assay provider. BlueBee solutions and services are available across all major European countries and the United States, as well as in Canada and Asia Pacific.
To learn more, visit www.bluebee.com and follow @bluebeegenomics.
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