Horovod
- "Horovod is a distributed training framework for TensorFlow, Keras, PyTorch, and MXNet. The goal of Horovod is to make distributed Deep Learning fast and easy to use. The primary motivation for this project is to make it easy to take a single-GPU TensorFlow program and successfully train it on many GPUs faster."
Quote from Horovod Github documentation.
metilene
metilene is a software tool to annotate differentally methylated regions (DMRs) and differentially methylated CpG sites (DMCs) from Methyl-seq data. metilene accounts for intra-group variances and offers different modes de-novo DMR detection, DMR detection within a known set of genomic features, and DMC detection. Various biological data can be used, metilene works with Whole-genome Bisulfite Sequencing (WGBS), Reduced representation bisulfite sequencing (RRBS), and any other input data, as long as absolute (methylation) levels and genomic coordinates are provided.
OSCprojects
Introduction
OSCprojects is a command developed at OSC for use on OSC's systems and is used to view your logged in accounts project information.
OSCgetent
Introduction
OSCgetent is a command developed at OSC for use on OSC's systems and is similar to the standard getent command. It lets one view group information.
OSCusage
Introduction
OSCusage is command developed at OSC for use on OSC's systems. It allows for a user to see information on their project's current RU balance, including which users and jobs incurred what charges.
HOWTO: Use a Conda Environment With Jupyter
Before Conda environments may be used by Jupyter Notebooks they must be installed so that Jupyter knows about them. Older versions of Conda automatically installed a Jupyter kernel for themselves, that installation process now must be performed manually by the user.
To perform the installation the user should load their prefered version of Python, activate their Conda environment and run the following command:
