This is a package for inference of protein activity from gene expression data. It includes the VIPER and msVIPER algorithms

This package is used for the detection of differentially expressed genes (DEGs) from the comparison of two biological conditions (treated vs. untreated, diseased vs. normal, mutant vs. wild-type) among different levels of gene expression (transcriptome ,translatome, proteome), using several statistical methods: Rank Product, Translational Efficiency, t-test, Limma, ANOTA, DESeq, edgeR. It also provides the possibility to plot the results with scatterplots, histograms, MA plots, standard deviation (SD) plots, coefficient of variation (CV) plots.

This package provides more than 9900 annotated position frequency matrices from 14 public sources, for multiple organisms.

DoRothEA is a gene regulatory network containing signed transcription factor. DoRothEA regulons, the collection of a TF and its transcriptional targets, were curated and collected from different types of evidence for both human and mouse. A confidence level was assigned to each TF-target interaction based on the number of supporting evidence.

This package implements the Signaling Pathway Impact Analysis (SPIA) which uses the information form a list of differentially expressed genes and their log fold changes together with signaling pathways topology, in order to identify the pathways most relevant to the condition under the study.

Non-parametric method for identifying differentially expressed (up- or down- regulated) genes based on the estimated percentage of false predictions (pfp). The method can combine data sets from different origins (meta-analysis) to increase the power of the identification.

GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. It is primarily designed for biochemical molecules like proteins, lipids and nucleic acids that have a lot of complicated bonded interactions, but since GROMACS is extremely fast at calculating the nonbonded interactions (that usually dominate simulations) many groups are also using it for research on non-biological systems, e.g. polymers. GROMACS supports all the usual algorithms you expect from a modern molecular dynamics implementation.

This package provides several cubic spline interpolation methods of H. Akima for irregular and regular gridded data are available through this package, both for the bivariate case and univariate case. Linear interpolation of irregular gridded data is also covered. A bilinear interpolator for regular grids was also added for comparison with the bicubic interpolator on regular grids.

The rfacts package is an R interface to the Fixed and Adaptive Clinical Trial Simulator FACTS. It programmatically invokes FACTS to run clinical trial simulations. It aggregates simulation output data into tidy data frames. These capabilities provide end-to-end automation for large-scale simulation pipelines, and they enhance computational reproducibility.

This package provides Python low-level bindings for NVIDIA CUDA toolkit.

This package decodes (demangles) low-level identifiers that have been mangled by CUDA C++ into user readable names. For every input alphanumeric word, the output of cu++filt is either the demangled name if the name decodes to a CUDA C++ name, or the original name itself.

This package provides an interface for generating PTX code from both binary and text NVVM IR inputs.

This package provides tooling to configure the NVSwitch memory fabrics to form one memory fabric among all participating GPUs, and monitors the NVLinks that support the fabric. See docs for more information.

This package provides the CUDA C++ developers with building blocks that make it easier to write safe and efficient code. It unifies three essential former CUDA C++ libraries into a single repository:

• Thrust (former repo)

• CUB (former repo)

• libcudacxx (former repo)

This package provides the CUDA compiler and the CUDA run-time support libraries for NVIDIA GPUs, all of which are proprietary.

This package provides the NVIDIA tool for debugging CUDA applications running. CUDA-GDB is an extension to GDB, the GNU Project debugger. The tool provides developers with a mechanism for debugging CUDA applications running on actual hardware. This enables developers to debug applications without the potential variations introduced by simulation and emulation environments.

This package provides a high-performance, GPU accelerated JPEG decoding functionality for image formats commonly used in deep learning and hyperscale multimedia applications. The library offers single and batched JPEG decoding capabilities which efficiently utilize the available GPU resources for optimum performance; and the flexibility for users to manage the memory allocation needed for decoding.

The nvJPEG library enables the following functions: use the JPEG image data stream as input; retrieve the width and height of the image from the data stream, and use this retrieved information to manage the GPU memory allocation and the decoding. A dedicated API is provided for retrieving the image information from the raw JPEG image data stream.

The encoding functions of the nvJPEG library perform GPU-accelerated compression of user’s image data to the JPEG bitstream. User can provide input data in a number of formats and colorspaces, and control the encoding process with parameters. Encoding functionality will allocate temporary buffers using user-provided memory allocator.

This package provides a C++ header-only library that wraps the NVIDIA CUDA Deep Neural Network library (cuDNN) C backend API. This entry point to the same API is less verbose (without loss of control), and adds functionality on top of the backend API, such as errata filters and autotuning.

This package provides the CUDA run-time support libraries for NVIDIA GPUs, all of which are proprietary.

This package provides a cross-platform API for annotating source code to provide contextual information to developer tools.

OpenCL (Open Computing Language) is a multi-vendor open standard for general-purpose parallel programming of heterogeneous systems that include CPUs, GPUs and other processors. This package provides the API to use OpenCL on NVIDIA GPUs.

The NVIDIA Management Library Headers (NVML) is a C-based API for monitoring and managing various states of the NVIDIA GPU devices. It provides a direct access to the queries and commands exposed via nvidia-smi.

This package provides a binary that prunes host object files and libraries to only contain device code for the specified targets.

This package provides cuFFT, the NVIDIA® CUDA® Fast Fourier Transform (FFT) product. It consists of two separate libraries: cuFFT and cuFFTW. The cuFFT library is designed to provide high performance on NVIDIA GPUs. The cuFFTW library is provided as a porting tool to enable users of FFTW to start using NVIDIA GPUs with a minimum amount of effort.

The FFT is a divide-and-conquer algorithm for efficiently computing discrete Fourier transforms of complex or real-valued data sets. It is one of the most important and widely used numerical algorithms in computational physics and general signal processing. The cuFFT library provides a simple interface for computing FFTs on an NVIDIA GPU, which allows users to quickly leverage the floating-point power and parallelism of the GPU in a highly optimized and tested FFT library. The cuFFTW library provides the FFTW3 API to facilitate porting of existing FFTW applications.