daniel-spies

daniel-spies's Stars

• Chechekhins/scParadise

  Highly accurate multi-task cell type annotation and surface protein abundance prediction

  Language:Jupyter Notebook1

• Masonze/scLEGA-main

  Language:Python2

• qjiangzhao/TEtrimmer

  TEtrimmer: a novel tool to automate manual curation of transposable elements

  Language:Python622

• carlodere/Transparent

  Language:Python1

• rasma774/TFTenricher

  Language:Python62

• fengzhanglab/Joung_TFAtlas_Manuscript

  Language:Python91

• JiangmeiRubyXiong/GammaGateR

  Language:HTML31

• biomap-research/scFoundation

  Language:Jupyter Notebook23537

• YingMa0107/IRIS

  Integrative and Reference-Informed Spatial Domain Detection for Spatial Transcriptomics

  Language:HTML251

• Linliu-Bioinf/SSGATE

  Language:Python1

• carmonalab/GeneNMF

  Methods to discover gene programs on single-cell data

  Language:R713

• LingyiC/CASCC

  CASCC: A co-expression assisted single-cell RNA-seq data clustering method

  Language:R6

• kurtsemih/copyVAE

  A variational autoencoder-based approach for copy number variation inference using single-cell transcriptomics

  Language:Python4

• LF-Yang/Code

  Language:Python4

• keita-iida/PSEUDOTIMEABC

  Workflow of pseudotime analysis and mathematical modeling using single-cell gene expression data

  1

• ChangSuBiostats/CS-CORE_python

  Python package for CS-CORE, a statistical method for cell-type-specific co-expression inference from single cell RNA-sequencing data

  Language:Jupyter Notebook6

• pathint/RankCompV3.jl

  RankCompV3: a differential expression analysis algorithm based on the relative expression orderings (REOs) of gene pairs

  Language:Julia6

• YingfanWang/PaCMAP

  PaCMAP: Large-scale Dimension Reduction Technique Preserving Both Global and Local Structure

  Language:Jupyter Notebook51152

• Janezjz/cellanova

  CellANOVA: Cell State Space Analysis of Variance for signal recovery in single cell batch integration

  Language:HTML14

• reimandlab/ActivePathways

  Integrative pathway enrichment analysis of multivariate omics data

  Language:R9923

• fansalon/TEspeX

  TEspeX - pipeline for Transposable Elements expression quantification

  Language:Python192

• JiekaiLab/scTE

  Language:Jupyter Notebook9727

• SONGDONGYUAN1994/ClusterDE

  A post-clustering differential expression (DE) method robust to false-positive inflation caused by double dipping

  Language:R234

• HaoWuLab-Bioinformatics/SCMcluster

  SCMcluster is an ensemble clustering algorithm for single-cell RNA sequencing data.

  Language:Python13

• davisidarta/topometry

  Systematically learn and evaluate manifolds from high-dimensional data

  Language:Python934

• Ken-Lau-Lab/AmbiQuant

  Quantification of scRNA-seq raw data quality

  Language:Jupyter Notebook2

• abelson-lab/scATOMIC

  Pan-Cancer Single Cell Classifier

  Language:R585

• AntonioDeFalco/SCEVAN

  R package that automatically classifies the cells in the scRNA data by segregating non-malignant cells of tumor microenviroment from the malignant cells. It also infers the copy number profile of malignant cells, identifies subclonal structures and analyses the specific and shared alterations of each subpopulation.

  Language:HTML9025

• LewisLabUCSD/secCellFie

  Expanding the CellFie tool to include the secretory pathway

  Language:HTML3

• earmingol/cell2cell

  User-friendly tool to infer cell-cell interactions and communication from gene expression of interacting proteins

  Language:Python5512