Deepbinner c261ae9-foss-2019b-Python-3.7.4

Deepbinner is a tool for demultiplexing barcoded Oxford Nanopore sequencing reads. It does this with a deep convolutional neural network classifier, using many of the architectural advances that have proven successful in image classification.

Accessing Deepbinner c261ae9-foss-2019b-Python-3.7.4

To load the module for Deepbinner c261ae9-foss-2019b-Python-3.7.4 please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):

module load Deepbinner/c261ae9-foss-2019b-Python-3.7.4

BEAR Apps Version

2019b

Architectures

EL8-cascadelake — EL8-haswell

The listed architectures consist of two part: OS-CPU.

  • BlueBEAR: The OS used on BlueBEAR is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.
  • BEAR and CaStLeS Cloud VMs: These VMs can have one of two OSes. Those with access to a BEAR Cloud or CaStLeS VM should check that the listed architectures for an application include the OS of VM being used. The VMs, irrespective of OS, will use the haswell CPU type.

Extensions

  • Deepbinner c261ae9
  • mappy 2.17
  • noise 1.2.2

More Information

For more information visit the Deepbinner website.

Dependencies

This version of Deepbinner has a direct dependency on: edlib/1.3.8.post1-foss-2019b-Python-3.7.4 foss/2019b Keras/2.3.1-foss-2019b-TensorFlow-1.15.0-Python-3.7.4 Python/3.7.4-GCCcore-8.3.0 TensorFlow/1.15.0-foss-2019b-Python-3.7.4

Other Versions

These versions of Deepbinner are available on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Version BEAR Apps Version
0.2.0-foss-2018b-Python-3.6.6 2018b

Last modified on 28th April 2020