CLC Assembly Cell is a high-performance computing solution for mapping reads to a reference and de novo assembly of next generation sequencing data.
With the command-line interface of CLC Assembly Cell, you can easily include its functionalities in scripts and other next generation sequencing workflows, and it's easy to install on your desktop computer or larger compute cluster. CLC Assembly Cell is accelerated through advanced algorithm implementations using the SIMD instruction set to parallelize and accelerate the most compute intensive parts of the algorithms. This makes the software one of the fastest and most accurate packages for NGS data analysis on the market.
Our new assembler is now part of CLC Assembly Cell - allowing rapid error correction and assembly of PacBio data. The read mapper has also been improved to better handle mapping of long reads such as PacBio sequencing reads.
Read more about CLC Assembly Cell
In the past several months, customers have performed remarkable work with CLC Genomics Workbench, a tool that offers customizable bioinformatics solutions for genomics, transcriptomics, epigenomics, and metagenomics. Many scientists rely on this tool for genome assembly and interpretation every day and here, we look at a handful of recent publications that have been supported by CLC Genomics Workbench.
De novo transcriptome assembly and comprehensive expression profiling in Crocus sativus to gain insights into apocarotenoid biosynthesis
First author: Mukesh Jain
This paper in Nature’s Scientific Reports journal comes from scientists in New Delhi who conducted transcriptome sequencing to better understand important biological mechanisms in saffron. They identified transcription factors, differentially expressed genes, and more. The team used CLC Genomics Workbench in the transcriptome assembly and the analysis of differentially expressed genes.
Complete coding sequence of Zika virus from Martinique outbreak in 2015
First author: G. Piorkowski
Scientists in France studied a strain of the Zika virus isolated from a patient in the Caribbean. In this publication, they report the full coding sequence of the virus, an essential resource for the ongoing battle against Zika virus. They used CLC Genomics Workbench to analyze the data generated with an Ion Torrent sequencer.
Effective de novo assembly of fish genome using haploid larvae
First author: Yuki Iwasaki
Published in the journal Gene, this marine genomics study from scientists in Japan demonstrates the utility of sequencing haploid fish larvae — in this case, yellowtail fish — to obtain a diploid genome assembly. They used the Proton sequencer and compared the performance of overlap-layout-consensus (OLC) and de Bruijn graph (DBG) assemblers. CLC Genomics Workbench, which uses a DBG approach, outperformed another tool in the study.
Isolation and Characterization of a Novel Gammaherpesvirus from a Microbat Cell Line
First author: Reed S. Shabman
This study, an editor’s pick in the mSphere journal, comes from scientists at the J. Craig Venter Institute and other organizations who were analyzing the transcriptome of a microbat when they discovered RNA from a previously unidentified herpesvirus. They used CLC Genomics Workbench for assembly and finishing of the viral genome.
Use of whole-genome sequencing to trace, control and characterize the regional expansion of extended-spectrum β-lactamase producing ST15 Klebsiella pneumoniae
First author: Kai Zhou
In this Scientific Reports paper, scientists from China and the Netherlands tracked the transmission path of a Klebsiella pneumoniae strain using genome-based phylogenetic analysis. They used a mapping unit in CLC Genomics Workbench to find genes associated with antibiotic resistance and pathogen virulence, and detected SNPs by mapping isolate sequence data with the same tool.
Read more about CLC Genomics Workbench
Take the first step in making the best out of your CLC Genomics Workbench workflow solution.
Our workbenches put practical bioinformatics in the hands of life scientists, and provide a smooth workflow solution from raw NGS data to interpretation, which you can use to generate biological insights.
Watch this webinar by Sr. Scientist Ajay Athavale to learn more about:
