56 Open source projects that are alternatives of or similar to scedar

k-means clustering algorithm with k-means++ initialization.

scisorseqr is an R-package for processing of single-cell long read data and analyzing differential isoform expression across any two conditions

A clustering tutorial with scikit-learn for beginners.

Implementing Genetic Algorithm on K-Means and compare with K-Means++

Implementation of the Neural Clustering Process algorithm in Pytorch

Single-cell Orientation Tracing

Differential expression analysis for single-cell RNA-seq data.

Code for the empty droplet and cell detection project from the HCA Hackathon.

David Mackay's book review and problem solvings and own python codes, mathematica files

Processing of single cell RNAseq data for the recovery of TCRs in python

Spatial Single Cell Analysis in Python

Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.

A collection of 50+ trajectory inference methods within a common interface 📥📤

Map SDK를 활용한 POI Clustering Interaction Dev.

Scripts to run and benchmark scRNA-seq cell cluster labeling methods

www.kelp-ml.org

Map SDK를 활용한 POI Clustering Interaction Dev

A R framework for pipeline benchmarking, with application to single-cell RNAseq

R package to visualize gene expression data based on weighted kernel density estimation

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

Different clustering approaches applied on different problemsets

Deep Learning based cell composition analysis with Scaden.

C4E, a JVM friendly library written in Scala for both local and distributed (Spark) Clustering.

All-in-one analysis pipeline

Wasserstein Generative Adversarial Network for analysing scRNAseq data

CellRank for directed single-cell fate mapping

interactive clustering platform

A Bayesian model for compositional single-cell data analysis

A high performance implementation of HDBSCAN clustering.

spatially-constrained clustering in R

Clustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview questions on clustering are also added in the end.

Fast OPTICS clustering in Cython + gradient cluster extraction

Implements "Clustering a Million Faces by Identity"

Genie++ Fast and Robust Hierarchical Clustering with Noise Point Detection - for Python and R

Implementation of ST-DBSCAN algorithm based on Birant 2007

Elixir implementation of CLOPE: A Fast and Effective Clustering Algorithm for Transactional Data

An intuitive implementation of spectral clustering on matlab

Cluster analysis library for Golang

ADENINE: A Data ExploratioN PipelINE

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Python Clustering Algorithms

Signac

tGPLVM: A Nonparametric, Generative Model for Manifold Learning with scRNA-seq experimental data

An unofficial demultiplexing strategy for SPLiT-seq RNA-Seq data

CellO: Gene expression-based hierarchical cell type classification using the Cell Ontology

No description or website provided.

Pipeline for initial analysis of droplet-based single-cell RNA-seq data

Stacked Denoising AutoEncoder based on TensorFlow

Manuscript for functional prediction of transcriptomic “dark matter” across species

Expression Weighted Celltype Enrichment. See the package website for up-to-date instructions on usage.

🐟 🔬🦀 alevin-fry is an efficient and flexible tool for processing single-cell sequencing data, currently focused on single-cell transcriptomics and feature barcoding.

An R implementation of the SINCERA pipeline for single cell RNA-seq profiling analysis

Discrete Distributional Differential Expression

Metacell - Single-cell mRNA Analysis

An online companion to the OSCA manuscript demonstrating Bioconductor resources and workflows for single-cell RNA-seq analysis.

scLearn：Learning for single cell assignment