Roger-GOAT

Roger-GOAT's Stars

• ageron/handson-ml2

  A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

  Language:Jupyter Notebook28.1k65651212.8k

• scverse/scvi-tools

  Deep probabilistic analysis of single-cell and spatial omics data

  Language:Python1.3k261k366

• smorabit/hdWGCNA

  High dimensional weighted gene co-expression network analysis

  Language:R371533336

• theislab/dca

  Deep count autoencoder for denoising scRNA-seq data

  Language:Python251116071

• juliasilge/supervised-ML-case-studies-course

  Supervised machine learning case studies in R! 💫 A free interactive tidymodels course

  Language:CSS224132976

• navinlabcode/copykat

  Language:R2171012055

• NBISweden/workshop-scRNAseq

  Single cell RNA sequencing analysis course

  Language:HTML199449101

• Teichlab/bbknn

  Batch balanced KNN

  Language:Python151104725

• tanaylab/metacell

  Metacell - Single-cell mRNA Analysis

  Language:R11058230

• tidymodels/tidymodels.org-legacy

  Legacy Source of tidymodels.org

  Language:HTML99811131

• klarman-cell-observatory/scPhere

  Language:Python9871214

• ShobiStassen/VIA

  trajectory inference

  Language:Jupyter Notebook9245021

• RausellLab/CelliD

  Gene signature extraction and cell-identity recognition at individual cell level from single-cell RNA-seq.

  Language:R9072119

• PaulingLiu/scibet

  A portable and fast single cell type identifier

  Language:R6211411

• CFeregrino/scWGCNA

  scWGCNA

  Language:HTML5631910

• bioinfoDZ/RISC

  A R package for integrated scRNA-seq data analysis using the RPCI algorithm

  Language:R442117

• andreariba/DeepCycle

  Cell cycle inference in single-cell RNA-seq

  Language:Python414187

• duct317/scDHA

  A tool for single-cell data analysis.

  Language:R382124

• jingshuw/SAVERX

  R package for transfer learning of single-cell RNA-seq denoising

  Language:R293309

• txWang/BERMUDA

  BERMUDA (Batch Effect ReMoval Using Deep Autoencoders) is a novel transfer-learning-based method for batch correction in scRNA-seq data.

  Language:Python284137

• AllonKleinLab/cospar

  Language:Python263296

• Apress/machine-learning-r-2e

  Source Code for 'Machine Learning Using R, Second Edition' by Karthik Ramasubramanian and Abhishek Singh

  Language:R175114

• WWXkenmo/ICAnet

  Independent Component Analysis decipher functional modules for better cell clustering and annotation

  Language:R16151

• gmstanle/coronary-progenitor-scRNAseq

  Language:HTML13204

• jwang-lab/scGNN

  scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks

  Language:Python11201

• iyhaoo/DISC

  A highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.

  Language:HTML10135

• Teichlab/spectrum-of-differentiation-supplements

  Mirror of analysis files for "Single-Cell RNA-Sequencing Reveals a Continuous Spectrum of Differentiation in Hematopoietic Cells"

  Language:Jupyter Notebook7515

• BMEngineeR/IRISFGM

  Development repository for the IRISFGM package for submission purposes

  Language:R6103

• keleslab/mlg

  Language:R2101

• TomKellyGenetics/bbknn

  Implementation of the BBKNN algorithm called by reticulate in R.

  Language:R2201