pseudotime

There are 15 repositories under pseudotime topic.

  • rezakj/iCellR

    Single (i) Cell R package (iCellR) is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST)).

    Language:R119133419

  • parashardhapola/scarf

    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.

    Language:Python9256212

  • alexisvdb/singleCellHaystack

    Finding surprising needles (=genes) in haystacks (=single cell transcriptome data).

    Language:R76589

  • LiQian-XC/sctour

    A deep learning architecture for robust inference and accurate prediction of cellular dynamics

    Language:Python503114
  • scFates

    LouisFaure/scFates

    a scalable python suite for tree inference and advanced pseudotime analysis from scRNAseq data.

    Language:Python482311

  • jr-leary7/scLANE

    Characterize gene dynamics over trajectories using GLMs, GEEs, & GLMMs.

    Language:R92812

  • BioBam/scMaSigPro

    Implementation of MaSigPro for scRNA-Seq Data

    Language:R8313
  • MiCV

    Cai-Lab-at-University-of-Michigan/MiCV

    MiCV is a python dash-based web-application that enables researchers to upload raw scRNA-seq data and perform filtering, analysis, and manual annotation.

    Language:CSS6300

  • Starlitnightly/scltnn

    A composite regression neural network for latent timing prediction of single-cell RNA-seq data

    Language:Jupyter Notebook5302

  • ardadurmaz/sc_eval

    Repository for benchmarking study of scRNA-Seq datasets for clustering and trajectory inference

    Language:R1101

  • auroramaurizio/my_RNA_seq_pipelines

    my_RNA_seq_pipelines

    Language:Jupyter Notebook0200

  • auroramaurizio/periferal_nerve_injury

    Bioinfo scripts for the analyses described in EXPERIMENTAL PROCEDURES section of "Structured wound angiogenesis instructs mesenchymal barrier compartments in the regenerating nerve" manuscript

    Language:Jupyter Notebook0202

  • inesmarais/scRNA-seq-analysis-cornea

    Scripts for analysis of transcriptomic data of the developing cornea

    Language:Jupyter Notebook0100

  • mode1990/Pseudotime-downstream-by-ML

    This script utilizes Monocle3 for inferring pseudotime and employs gradient boosting machine learning (xgboost) to identify genes predictive of pseudotime. Subsequently, it fits a regression model using these newly identified genes.

    Language:R0100

  • Stfort52/NOLAN

    TENET refined

    Language:Python10