pseudotime

There are 0 repository under pseudotime topic.

rezakj / iCellR
iCellR is an interactive R package designed to facilitate the analysis and visualization of high-throughput single-cell sequencing data. It supports a variety of single-cell technologies, including scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq, and Spatial Transcriptomics (ST).
singel-cell-sequencing clustering-algorithm clustering normalization umap pseudotime scrna-seq scvdj-seq cite-seq 3d intractive-graph 10xgenomics dropout batch-normalization imputation diffusion-maps cell-type-classification icellr
Language:R 124
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.
bioinformatics single-cell-genomics single-cell-rna-seq dimension-reduction clustering umap tsne big-data cite-seq single-cell-atac-seq memory-efficient scalable-data-analysis scrna-seq scatac-seq pseudotime multiomics gene-modules differential-expression graph-analytics genomics
Language:Python 104
alexisvdb / singleCellHaystack
Finding surprising needles (=genes) in haystacks (=single cell transcriptome data).
bioinformatics single-cell r transcriptomics spatial-transcriptomics cite-seq pseudotime scatac-seq spatial-proteomics
Language:R 85
LiQian-XC / sctour
A deep learning architecture for robust inference and accurate prediction of cellular dynamics
deep-learning single-cell-genomics inference-and-prediction latent-space pseudotime vector-field
Language:Python 68
scFates
LouisFaure / scFates
a scalable python suite for tree inference and advanced pseudotime analysis from scRNAseq data.
tree-inference elpigraph pseudotime scrnaseq
Language:Python 60
BioBam / scMaSigPro
Implementation of MaSigPro for scRNA-Seq Data
pseudotime single-cell-rna-seq time-series trajectory-analysis
Language:R 14
jr-leary7 / scLANE
Characterize gene dynamics over trajectories using GLMs, GEEs, & GLMMs.
scrna-seq single-cell pseudotime trajectory-inference rna-velocity differential-expression estimating-equations genomics mixed-models transcriptomics
Language:R 12
Noble-Lab / Sceptic
Pseudotime analysis for time-series single-cell sequencing and imaging data
pseudotime single-cell-imaging single-cell-rna-seq time-series
Language:Jupyter Notebook 12
Starlitnightly / scltnn
A composite regression neural network for latent timing prediction of single-cell RNA-seq data
pseudotime python scrna-seq
Language:Jupyter Notebook 9
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.
gene-expression scanpy pseudotime pseudotime-trajectory marker-genes umap-projection clustering anndata leiden
Language:CSS 7
ardadurmaz / sc_eval
Repository for benchmarking study of scRNA-Seq datasets for clustering and trajectory inference
clustering pseudotime scrna-seq
Language:R 1
auroramaurizio / my_RNA_seq_pipelines
my_RNA_seq_pipelines
bulk-rna-seq bulk-rna-seq-deconvolution dge plots pseudotime rna-seq scrna-seq trajectory velocity
Language:Jupyter Notebook 1
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
bulkrnaseq deconvolution pseudotime scrna-seq velocity cell-cell-communication nerve injury
Language:Jupyter Notebook 1
inesmarais / scRNA-seq-analysis-cornea
Scripts for analysis of transcriptomic data of the developing cornea
corneal development heatmap pseudotime python python3 scatac-seq scfates scrna-seq scrna-seq-analysis
Language:Jupyter Notebook 1
MargaritaLiarou1 / TimeFlow
TimeFlow: a density-driven pseudotime method for flow cytometry data analysis.
density-estimation normalizing-flows pseudotime trajectory-inference bone-marrow-data flow-cytometry-analysis
Language:Jupyter Notebook 1
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.
machine-learning pseudotime single-cell
Language:R 0
Stfort52 / NOLAN
TENET refined
gene-regulatory-network gene-regulatory-network-inference pseudotime single-cell single-cell-rna-seq transfer-entropy
Language:Python

pseudotime

rezakj / iCellR

parashardhapola / scarf

alexisvdb / singleCellHaystack

LiQian-XC / sctour

LouisFaure / scFates

BioBam / scMaSigPro

jr-leary7 / scLANE

Noble-Lab / Sceptic

Starlitnightly / scltnn

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

ardadurmaz / sc_eval

auroramaurizio / my_RNA_seq_pipelines

auroramaurizio / periferal_nerve_injury

inesmarais / scRNA-seq-analysis-cornea

MargaritaLiarou1 / TimeFlow

mode1990 / Pseudotime-downstream-by-ML

Stfort52 / NOLAN