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Strand NGS is supported on Windows, Mac OS X, and Linux platforms. The specific versions supported for each platform are as follows:
Windows - Windows 7, Windows 8, and Windows 10 Mac OS X - Up to Mac OS 10.12 (Sierra) Linux - The tool should work on any flavour of Linux, but has been tested on Red Hat Enterprise Linux (up to v6.5), Debian GNU/Linux up to 9.0 (Stretch) and Ubuntu up to 16.04 LTS
The architectures supported in all the cases above include both 32-bit x86 compatible and 64-bit x86-64 compatible architectures. Intel Itanium (IA-64), Mac Power PC (PPC), Sun SPARC, IBM POWER and other such architectures are not supported.
Strand NGS is optimized to make the best use of the available hardware resources. The minimum hardware requirements for Strand NGS are actually quite minimal. Analysis of most samples, including large whole genome studies, can be done on regular desktop machines with ease. But obviously, the bigger and better the machine, the more productive Strand NGS will be.
General guidelines for hardware configurations, depending on the size of the datasets you wish to analyze, are as follows:
1. Small size - Several experiments containing a couple of samples with up to 10 million reads or so can be easily analyzed on a 32-bit machine with 4 GB RAM, 2 GHz dual-core processor and about 300 GB hard disk space.
2. Medium size - Several experiments containing around 10 samples with about 50 million reads or so can be analyzed on a 64-bit machine with 8 GB RAM, 2 GHz quad-core processor, and about 500 GB of hard disk space.
3. Large size - For whole genome experiments with large coverages, or experiments with large number of samples, a 64-bit machine with 16 GB RAM, two 2 GHz quad-core processors, and about 1 TB of disk space should work fine.
These are of course general guidelines. We often try all kinds of experiments on different kinds of machines - from regular laptops to high-end servers and EC2 cloud instances. Here are some examples of storage and computation requirements results, but don't hesitate to contact us if you would like any further advice on a solution that would work best for your needs.
Compute and storage requirements depend on the number / size of the samples and the type of computation. More RAM and higher processor power on compute worker directly translate to higher throughput.
Here are the requirements for an example scenario:
1000 human exome samples each with ~100M reads of 100bp length
Server Machine
Storage Size NFS mounted NAS with 10TB
Compute Nodes
To process 200 samples in a month, three Compute Nodes would be needed, each with: 2 Quad Core Intel Xeon CPUs at 3GHz, 16GB RAM. In case of alignment of human genome samples, 20GB RAM is recommended for optimal performance. 200GB of local HDD storage. 1Gbps+ LAN connection between Server, Compute Node and NAS. Running on 64-bit Linux.
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