Create your own pipeline in seconds. Use defaults or define specific parameters. It's your choice!
Meet EvE, the first universal genetic adaptor that aligns, calls, annotates, converts and interprets almost any genetic data file to EvErything. EvE includes a straightforward user interface and powerful, dynamic processing so that using your custom EvE pipeline is effortless and fast.
With EvE, you can create your own custom pipeline within seconds. For example, you can select Isaac for alignment and SamTools for variant calling. Or you can select CutAdapt for pre-processing, TopHat2 for alignment, Isaac for variant calling and SnpEff for annotation. Once you select your pipeline, you can use defaults or easily modify almost any parameter.
You no longer have to worry about whether your computer hardware and servers are powerful enough to process your data. With EvE, you also don't have to worry about bandwidth charges or obscure cloud computing fees. All you need is an internet connection (such as from a laptop or mobile device) and EvE will process your genetic data.
If a conversion is only possible in EvE Premium then this conversion will still appear in EvE Free but will not be able to be selected (it will appear as an 'inactive' selection).
EvE accepts almost all file formats including .bz2 and .gz compression.
EvE also accepts inputs generated using any reference genome from hg2 through the latest patch releases of GRCh38.
|Isaac Variant Caller|
HPG BigData (AVRO)
This simple yet secure approach means you no longer have to use your own storage or computing power to conduct genetic analysis and you also no longer have to use USB drives or FTP sites to move and share genetic data.
EvE includes an integration of the following:
A suite of programs for interacting with high-throughput sequencing data. It consists of three separate repositories:
GATK (Genome Analysis Toolkit)
GATK analyzes high-throughput sequencing data. The toolkit, which focuses on providing high quality data, offers a wide variety of tools including variant discovery and genotyping.
Isaac Variant Caller
Isaac Variant Caller (IVC) is an analysis package designed to detect SNVs and small indels from the aligned sequencing reads of a single diploid sample.
SnpEFF predicts the effects of genetic variations and also provides annotations. Annotations can simple such as variant name or more complex such as site of variation such as exon, intron and its effect on gene expression.
Since EvE offers conversions between different file formats such which is a multistep process at time, we use our own scripts to pipe data and create some file types.
The following use custom scripts developed by Sequencing.com:
Wormtable is a format for storing large scale tabular data and interacting with it. It generates an index file as well that can be used repeatedly. Wormtable files are considered very Python friendly and can be used in downstream Python based analysis.
GVF (Genome Variation Format) is gaining popularity as a standard for sequence ontology based datasets. It is a successor of the GFF3 format and includes pragmas for defining sequence alterations at genomic locations as compared to the reference genome.
Human clinical applications require sequencing information for both variant and non-variant positions, yet there is currently no common exchange format for such data. Genomic VCF (gVCF) addresses this issue. gVCF is a set of conventions applied to the standard variant call format (VCF) that include genotype, annotation and other information across all sites in the genome in a reasonably compact format.
Isaac Variant Caller
This app is designed for researchers, bioinformatics experts and genomics professionals. The genetic analysis and statements that appear in this app have not been evaluated by the United States Food and Drug Administration. The Sequencing.com website and all software applications (Apps) that use Sequencing.com's website, as well as Sequencing.com's open Application Programming Interface (API), are not intended to diagnose, treat, cure, or prevent any disease.