NicheNet: predict active ligand-target links between interacting cells
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Updated
Aug 20, 2024 - R
NicheNet: predict active ligand-target links between interacting cells
A repository for setting up a RNAseq workflow
Table of software for the analysis of single-cell RNA-seq data.
zUMIs: A fast and flexible pipeline to process RNA sequencing data with UMIs
Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data
Color blindness friendly visualization of single-cell and bulk RNA-sequencing data
Reference-guided transcript discovery and quantification for long read RNA-Seq data
Batch effect adjustment based on negative binomial regression for RNA sequencing count data
Cell type annotation with local Large Language Models (LLMs) - Ensuring privacy and speed with extensive customized reports
Visual self-service analytics platform for big omics data.
Infer cell types in scRNA-seq data using bulk RNA-seq or gene sets
Statistical Analysis of RNA-Seq Tools
integrated RNA-seq Analysis Pipeline
SIB course on single cell transcriptomics by mostly using the Seurat pipeline
Repository for the R package EPIC, to Estimate the Proportion of Immune and Cancer cells from bulk gene expression data.
Convert Counts to Fragments per Kilobase of Transcript per Million (FPKM)
π π π―π¨π₯π effortlessly translates differential expression datasets and RNAseq data into informative volcano plots. Highlight genes of interest with unprecedented ease. With just a single line of code, visualize complex datasets, gaining deeper insights and simplifying data representation
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