Plot_ly-based plotting functions for use with Seurat objects
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Updated
May 15, 2019 - R
Plot_ly-based plotting functions for use with Seurat objects
R package - Analysis of Single Cell Expression, Normalisation and Differential expression (ascend)
Create violin plots of gene expression for multiple genes
Display gene expression along a given reduced dimension on a heatmap
Binary Factor Analysis: a dimensionality reduction tool for noisy, high throughput single cell genomic data
R package: {rfca} Random forest-based cell annotation methods for scRNAseq analysis. {rfca} contains methods which identifies cell types using machine learning trained on a diversity of cell types, without the need for a labelled training dataset. It also allows you to train your own cell prediction models with your own labels (cell type, subtyp…
I've written a few functions that help me look through scRNA-seq data while working with Seurat.
scRNA-seq datasets to support Jung et al, Sci Adv, 7(6): eabe5735, 2021. DOI: 10.1126/sciadv.abe5735
Intercellular communication analysis for scRNA-seq data
R package for single-cell RNA-sequencing analysis
Novel joint clustering method with scRNA-seq and CITE-seq data
Comparison of batch correction methods for scRNA-seq data - basically a clone of BatchBench
A bit of code to interconvert objects between the Seurat and RISC environments for scRNA-seq data analysis
scRNA-marker-gene-Annotation.
iDA: dimensionality reduction for latent structure discovery
Objectives are to: Optimise the scRNA-seq data approach using Seurat by investigating the effects of QC and background correction for healthy and a diabetic dataset of the mouse retina. Perform differential gene expression. Perform clustering of the different retinal cell types from the scRNA-Seq data by assessing a range of publicly avail…
Calculate spatial correlation between two genes of a Seurat-format spatial scRNA-seq data
Simultaneous analysis of genes and transposable elements (TEs) from 10X scRNAseq datasets derived from CD and NIBD samples using Alevin.
The following repository contains code for all scRNAseq analysis and visualization performed in the paper: Single cell resolution analysis of the human pancreatic ductal progenitor cell niche
The R script and relative data set for Integrated single-cell transcriptomics and proteomics reveal cellular-specific response and microenvironment remodeling in aristolochic acid nephropathy
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