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anu-bioinfo's Projects

scbatchpaper icon scbatchpaper

Code used for the single-cell RNA-Seq batch effects paper

scdeepsort icon scdeepsort

Reference-free Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network

scdney icon scdney

Single cell data integrative analysis

scenicprotocol icon scenicprotocol

A scalable SCENIC workflow for single-cell gene regulatory network analysis

scgen icon scgen

Single cell perturbation prediction

sci-fate_analysis icon sci-fate_analysis

Downstream analysis script for sci-fate (TF-gene linkage analysis / cell linkage analysis)

scnn icon scnn

Survival Convolutional Neural Networks

scrna2019 icon scrna2019

supporting code for the multinomial single cell RNA-Seq paper

scrnagan icon scrnagan

Training Generative Adversarial Network models for scRNA-seq datasets

sctyper icon sctyper

scTyper: a comprehensive pipeline for the cell typing analysis of single-cell RNA-seq data

sg-nex-data icon sg-nex-data

Nanopore RNA-Seq data from the Singapore Nanopore-Expression Project

single-cell-analysis-flow-cytometry icon single-cell-analysis-flow-cytometry

To reveal the cellular heterogeneity within flow cytometry data, clustering and pseudotime analysis can be performed. Here, we demonstrate how to import (clustered) data, how to apply clustering and dimensionality reduction, and how to apply pseudotime analysis by Slingshot.

singlecell_pnm icon singlecell_pnm

:sparkles: Code and figures accompanying the paper, "Single-cell alternative splicing analysis with Expedition reveals splicing dynamics during neuron differentiation" by Song and Botvinnik, et al

singlesplice icon singlesplice

Algorithm for detecting alternative splicing in a population of single cells. See details in Welch et al., Nucleic Acids Research 2016: http://nar.oxfordjournals.org/content/early/2016/01/05/nar.gkv1525.full

snatac icon snatac

Ren Lab in-house dual-barcode single nucleus ATAC-seq (snATAC-seq) analysis pipeline

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