Archive by Author | Ilya Chorny

New RNA-Seq Alignment App with support for TruSight RNA Pan-Cancer and more

With the launch of the TruSight RNA Pan-Cancer panel, a targeted enrichment panel for the detection of variants, fusions, and gene expression profiles in 1385 cancer-associated genes, Illumina is pleased to provide an intuitive BaseSpace App, RNA-Seq Alignment v 1.0, that supports simple push button analysis of the data.

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RNA-Seq Alignment

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Illumina software now available under GPL v3

We are excited to announce that we will be contributing Illumina’s secondary analysis software to the open source community under the GPL v3 license. The software can be found on GitHub (https://github.com/illumina). Currently available software include the Isaac aligner and the Manta structural variant caller (manuscript submitted). Other tools such as the Starling small variant caller, Strelka somatic variant caller, the Canvas copy number caller, and Haplotype Compare (a.k.a hap.py) for comparing variant call sets will be made available soon. Additional tools will also be made available as they are developed and deployed. With these efforts we are also committing to publication of our methods in high impact peer reviewed journals.

We look forward to working with the open source community to provide high quality secondary analysis tools that will help enable discoveries with next generation sequencing data.

 

MethylSeq v1.0 App for DNA Methylation Calling

DNA methylation is one of the most studied epigenetic modifications in human cells. Changes in DNA methylation patterns play a critical role in development, differentiation and diseases such as multiple sclerosis, diabetes, schizophrenia, aging, and multiple forms of cancer. Over the past decade, interest in DNA methylation has grown rapidly and expanded across multiple areas of research. Consequently, DNA methylation analysis methods have undergone dramatic changes. Bisulfite-treatment and next-generation sequencing (NGS) have increasingly become the tools of choice to profile DNA methylation levels. Here, we announce a bioinformatics solution for analyzing NGS methylation data: BaseSpace® MethylSeq v1.0 app.

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MethylSeq v1.0 app

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New RNA Apps in BaseSpace

We are excited to launch the TruSeq Targeted RNA v1.0 and Small RNA v1.0 Core Apps in BaseSpace, which are some of the most feature-rich Apps we have launched to date.

 

TruSeq Targeted RNA v1.0

Small RNA v1.0

A high level overview of the Apps is provided below. More detailed information about the Apps can be found in their respective Core Apps application guides.

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New and Updated BaseSpace Apps

It’s been an exciting last 30 days for App releases. At the end of February we released v1.1 of the TruSeq Long-Read Assembly and the TruSeq Phasing Analysis Apps.

 

TruSeq Long-Read Assembly v1.1

TruSeq Phasing Analysis Apps v1.1

These updates were mainly to improve the performance of the Apps and to fix a few minor bugs. Detailed information can be found in the customer release note.

We also released v2.1 of the Isaac Enrichment and BWA Enrichment Apps.

Isaac Enrichment v2.1

BWA Enrichment v2.1

These updates allow the Apps to take advantage of the multi-launch feature available in the BaseSpace platform. Users can now analyze up to 96 samples in parallel across multiple nodes dramatically reducing the time to answer. 96 samples can now be analyzed in as little as 2 hours on a 50x exome. Detailed information can be found in the customer release note.

We also published a handfull of new 3rd Party Apps.

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Prokka small genome annotation is now in BaseSpace Apps.

We are pleased to announce the release of our latest BaseSpace Labs App Prokka Genome Annotation.

 

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Prokka wraps the tool of the same name developed by Dr. Torsten Seemann of the Victoria Bioinformatics Consortium. Prokka automates the process of building an annotation of a prokaryotic genome, first running a comprehensive set of feature prediction tools then combining their output into standards-compliant files suitable for further analysis, visualization in genome browsers or submission to archives.

As input, the Prokka App requires a FASTA file which is assumed by default to contain assembled contigs from a bacterial or other prokaryotic genome, such as produced by the SPAdesVelvet de novo Assembly or DNAStar Assemble bacteria Apps. Shotgun metagenomic data can also be annotated by making the appropriate selection on the input form. An example of the App’s output can be found here.

Citation: Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014 Jul 15;30(14):2068-9. PMID:24642063