rvangara

SigProfilerAssignment

Assignment of known mutational signatures to individual samples and individual somatic mutations

SigProfilerExtractor

SigProfilerExtractor allows de novo extraction of mutational signatures from data generated in a matrix format. The tool identifies the number of operative mutational signatures, their activities in each sample, and the probability for each signature to cause a specific mutation type in a cancer sample. The tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.

SigProfilerMatrixGenerator

SigProfilerMatrixGenerator creates mutational matrices for all types of somatic mutations. It allows downsizing the generated mutations only to parts for the genome (e.g., exome or a custom BED file). The tool seamlessly integrates with other SigProfiler tools.

SigProfilerPlotting

SigProfilerPlotting provides a standard tool for displaying all types of mutational signatures as well as all types of mutational patterns in cancer genomes. The tool seamlessly integrates with other SigProfiler tools.

CLAM

Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering

ColossalAI

Making large AI models cheaper, faster and more accessible

DnMFk

A C++ framework of Distributed Non-Negative Matrix Factorization implementation to find Latent Dimensionality in Big Data

pyDNMFk

Python Distributed Non Negative Matrix Factorization with custom clustering

SigProfilerExtractor

SigProfilerExtractor allows de novo extraction of mutational signatures from data generated in a matrix format. The tool identifies the number of operative mutational signatures, their activities in each sample, and the probability for each signature to cause a specific mutation type in a cancer sample. The tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.

stable-diffusion-text-to-image

A latent text-to-image diffusion model

rvangara/CLAM

Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering

rvangara/ColossalAI

Making large AI models cheaper, faster and more accessible

rvangara/DnMFk

A C++ framework of Distributed Non-Negative Matrix Factorization implementation to find Latent Dimensionality in Big Data

rvangara/pyDNMFk

Python Distributed Non Negative Matrix Factorization with custom clustering

rvangara/SigProfilerExtractor

SigProfilerExtractor allows de novo extraction of mutational signatures from data generated in a matrix format. The tool identifies the number of operative mutational signatures, their activities in each sample, and the probability for each signature to cause a specific mutation type in a cancer sample. The tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.

rvangara/stable-diffusion-text-to-image

A latent text-to-image diffusion model

rvangara/PRMLT

Matlab code for machine learning algorithms in book PRML

rvangara/pyDNTNK

Python Distributed Non Negative Tensor Networks

rvangara/rvangara

My Personal Github repo

rvangara/Same-Size-K-Means-Clustering

This is a variation of the k-means clustering that produces equally sized clusters.

rvangara/SignatureAnalyzer-GPU

GPU implementation of ARD NMF

rvangara/accelerated-computing-hub

NVIDIA curated collection of educational resources related to general purpose GPU programming.

rvangara/Generative-AI-with-Large-Language-Models-Coursera

Notes and coding notebooks of Coursera course - Generative AI with Large Language Models (LLMs)

rvangara/openslide

C library for reading virtual slide images

rvangara/pyHNMFk

The identification of sources of advection-diffusion transport is based usually on solving complex ill-posed inverse models against the available state-variable data records.

rvangara/SigProfilerAssignment-self

Assignment of known mutational signatures to individual samples and individual somatic mutations

rvangara/starter-research-group

rvangara/Tramonto

Primary source code repository for the nanoscience code Tramonto.