single-cell RNA-seq 工具大全
【怪毛匠子-整理】
awesome-single-cell
List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc. Contributions welcome...
- anchor - [Python] - ⚓ Find bimodal, unimodal, and multimodal features in your data
- BackSPIN - [Python] - Biclustering algorithm developed taking into account intrinsic features of single-cell RNA-seq experiments.
- BASiCS - [R] - Bayesian Analysis of single-cell RNA-seq data. Estimates cell-specific normalization constants. Technical variability is quantified based on spike-in genes. The total variability of the expression counts is decomposed into technical and biological components. BASiCS can also identify genes with differential expression/over-dispersion between two or more groups of cells.
- bonvoyage - [Python] -
Transform percentage-based units into a 2d space to evaluate changes in distribution with both magnitude and direction.
- BPSC - [R] - Beta-Poisson model for single-cell RNA-seq data analyses
- Cellity - [R] - Classification of low quality cells in scRNA-seq data using R
- cellTree - [R] - Cell population analysis and visualization from single cell RNA-seq data using a Latent Dirichlet Allocation model.
- clusterExperiment - [R] - Functions for running and comparing many different clusterings of single-cell sequencing data. Meant to work with SCONE and slingshot.
- ECLAIR - [python] - ECLAIR stands for Ensemble Clustering for Lineage Analysis, Inference and Robustness. Robust and scalable inference of cell lineages from gene expression data.
- embeddr - [R] - Embeddr creates a reduced dimensional representation of the gene space using a high-variance gene correlation graph and laplacian eigenmaps. It then fits a smooth pseudotime trajectory using principal curves.
- Falco - [AWS cloud] - Falco: A quick and flexible single-cell RNA-seq processing framework on the cloud.
- FastProject - [Python] - Signature analysis on low-dimensional projections of single-cell expression data.
- flotilla - [Python] Reproducible machine learning analysis of gene expression and alternative splicing data
- GiniClust - [Python/R] - GiniClust is a clustering method implemented in Python and R for detecting rare cell-types from large-scale single-cell gene expression data. GiniClust can be applied to datasets originating from different platforms, such as multiplex qPCR data, traditional single-cell RNAseq or newly emerging UMI-based single-cell RNAseq, e.g. inDrops and Drop-seq.
- HocusPocus - [R] - Basic PCA-based workflow for analysis and plotting of single cell RNA-seq data.
- M3Drop - [R] - Michaelis-Menten Modelling of Dropouts for scRNASeq.
- MAST - [R] - Model-based Analysis of Single-cell Transcriptomics (MAST) fits a two-part, generalized linear models that are specially adapted for bimodal and/or zero-inflated single cell gene expression data.
- Monocle - [R] - Differential expression and time-series analysis for single-cell RNA-Seq.
- OEFinder - [R] - Identify ordering effect genes in single cell RNA-seq data. OEFinder shiny impelemention depends on packages shiny, shinyFiles, gdata, and EBSeq.
- Ouija - [R] - Incorporate prior information into single-cell trajectory (pseudotime) analyses using Bayesian nonlinear factor analysis.
- outrigger - [Python] - Outrigger is a program to calculate alternative splicing scores of RNA-Seq data based on junction reads and a de novo, custom annotation created with a graph database, especially made for single-cell analyses.
- PoissonUMIs - [R] - Poisson Modelling of scRNASeq UMI counts.
- SAKE - [R] - Single-cell RNA-Seq Analysis and Clustering Evaluation.
- SC3 - [R] - SC3 is a tool for the unsupervised clustering of cells from single cell RNA-Seq experiments.
- scater - [R] - Scater places an emphasis on tools for quality control, visualisation and pre-processing of data before further downstream analysis, filling a useful niche between raw RNA-sequencing count or transcripts-per-million data and more focused downstream modelling tools such as monocle, scLVM, SCDE, edgeR, limma and so on.
- scDD - [R] - scDD (Single-Cell Differential Distributions) is a framework to identify genes with different expression patterns between biological groups of interest. In addition to traditional differential expression, it can detect differences that are more complex and subtle than a mean shift.
- SCDE - [R] - Differential expression using error models and overdispersion-based identification of important gene sets.
- SCell - [matlab] - SCell is an integrated software tool for quality filtering, normalization, feature selection, iterative dimensionality reduction, clustering and the estimation of gene-expression gradients from large ensembles of single-cell RNA-seq datasets. SCell is open source, and implemented with an intuitive graphical interface.
- SCIMITAR - [Python] - Single Cell Inference of Morphing Trajectories and their Associated Regulation module (SCIMITAR) is a method for inferring biological properties from a pseudotemporal ordering. It can also be used to obtain progression-associated genes that vary along the trajectory, and genes that change their correlation structure over the trajectory; progression co-associated genes.
- scLVM - [R] - scLVM is a modelling framework for single-cell RNA-seq data that can be used to dissect the observed heterogeneity into different sources, thereby allowing for the correction of confounding sources of variation. scLVM was primarily designed to account for cell-cycle induced variations in single-cell RNA-seq data where cell cycle is the primary soure of variability.
- SCONE - [R] - SCONE (Single-Cell Overview of Normalized Expression), a package for single-cell RNA-seq data quality control (QC) and normalization. This data-driven framework uses summaries of expression data to assess the efficacy of normalization workflows.
- SCORPIUS - [R] - SCORPIUS an unsupervised approach for inferring developmental chronologies from single-cell RNA sequencing data. It accurately reconstructs trajectories for a wide variety of dynamic cellular processes. The performance was evaluated using a new, quantitative evaluation pipeline, comparing the performance of current state-of-the-art techniques on 10 publicly available single-cell RNA sequencing datasets. It automatically identifies marker genes, speeding up knowledge discovery.
- SCOUP - [C++] - Uses probabilistic model based on the Ornstein-Uhlenbeck process to analyze single-cell expression data during differentiation.
- scran - [R] - This package implements a variety of low-level analyses of single-cell RNA-seq data. Methods are provided for normalization of cell-specific biases, pool-based norms to estimate size factors, assignment of cell cycle phase, and detection of highly variable and significantly correlated genes.
- SCRAT - [R] - SCRAT provides essential tools for users to read in single-cell regolome data (ChIP-seq, ATAC-seq, DNase-seq) and summarize into different types of features. It also allows users to visualize the features, cluster samples and identify key features.
- scTCRseq - [python] - Map T-cell receptor (TCR) repertoires from single cell RNAseq.
- SCUBA - [matlab/R] - SCUBA stands for "Single-cell Clustering Using Bifurcation Analysis." SCUBA is a novel computational method for extracting lineage relationships from single-cell gene expression data, and modeling the dynamic changes associated with cell differentiation.
- SEPA - [R] - SEPA provides convenient functions for users to assign genes into different gene expression patterns such as constant, monotone increasing and increasing then decreasing. SEPA then performs GO enrichment analysis to analysis the functional roles of genes with same or similar patterns.
- Seurat - [R] - It contains easy-to-use implementations of commonly used analytical techniques, including the identification of highly variable genes, dimensionality reduction (PCA, ICA, t-SNE), standard unsupervised clustering algorithms (density clustering, hierarchical clustering, k-means), and the discovery of differentially expressed genes and markers.
- sincell - [R] - Existing computational approaches for the assessment of cell-state hierarchies from single-cell data might be formalized under a general workflow composed of i) a metric to assess cell-to-cell similarities (combined or not with a dimensionality reduction step), and ii) a graph-building algorithm (optionally making use of a cells-clustering step). Sincell R package implements a methodological toolbox allowing flexible workflows under such framework.
- sincera - [R] - R-based pipeline for single-cell analysis including clustering and visualization.
- SinQC - [R] - A Method and Tool to Control Single-cell RNA-seq Data Quality.
- SLICER - [R] - Selective Locally linear Inference of Cellular Expression Relationships (SLICER) algorithm for inferring cell trajectories.
- slingshot - [R] - Functions for identifying and characterizing continuous developmental trajectories in single-cell sequencing data.
- SPADE - [R] - Visualization and cellular hierarchy inference of single-cell data using SPADE.
- switchde - [R] - Differential expression analysis across pseudotime. Identify genes that exhibit switch-like up or down regulation along single-cell trajectories along with where in the trajectory the regulation occurs.
- TraCeR - [python] - Reconstruction of T-Cell receptor sequences from single-cell RNA-seq data.
- TRAPeS - [python, C++] - TRAPeS (TCR Reconstruction Algorithm for Paired-End Single-cell), a software for reconstruction of T cell receptors (TCR) using short, paired-end single-cell RNA-sequencing.
- TSCAN - [R] - Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis.
- Gingko - [R, C] - Gingko is a cloud-based web app single-cell copy-number variation analysis tool.
- Aaron Lun's Single Cell workflow on Bioconductor - [R] - This article describes a computational workflow for basic analysis of scRNA-seq data using software packages from the open-source Bioconductor project.
- Bioconductor2016 Single-cell-RNA-sequencing workshop by Sandrine Dudoit lab - [R] - SCONE, clusterExperiment, and slingshot tutorial.
- BiomedCentral Single Cell Omics collectin - collection of papers describing techniques for single-cell analysis and protocols.
- CSHL Single Cell Analysis - Bioinformatics course materials - Uses Shalek 2013 and Macaulay 2016 datasets to teach machine learning to biologists
- Festival of Genomics California Single Cell Workshop - [R] - Explores basic workflow from exploratory data analysis to normalization and downstream analyses using a dataset of 1679 cells from the Allen Brain Atlas.
- Gilad Lab Single Cell Data Exploration - R-based exploration of single cell sequence data. Lots of experimentation.
- Harvard STEM Cell Institute Single Cell Workshop 2015 - workshop on common computational analysis techniques for scRNA-seq data from differential expression to subpopulation identification and network analysis. See course description for more information
- Hemberg Lab scRNA-seq course materials
- Using Seurat for unsupervised clustering and biomarker discovery - 301 single cells across diverse tissues from (Pollen et al., Nature Biotechnology, 2014)
- Using Seurat for spatial inference in single-cell data - 851 single cells from Zebrafish embryogenesis (Satija, Farrell et al., Nature Biotechnology, 2015)
- ASAP - Automated Single-cell Analysis Pipeline (https://f1000research.com/posters/5-1441).
- conquer - A repository of consistently processed, analysis-ready single-cell RNA-seq data sets.
- Neuro Single Cell Expression Portal at the Broad - The Single-Cell RNA-Seq Portal for Brain Research was developed to facilitate sharing scientific results, and disseminate datasets resulting from the NIH's BRAIN initiative.
- SAKE - Single-cell RNA-Seq Analysis and Clustering Evaluation.
Journal articles of general interest
- Comparative analysis of single-cell RNA sequencing methods - a comparison of wet lab protocols for scRNA sequencing.
- CrazyHotTommy's RNA-seq analysis list - Very broad list that includes some single cell RNA-seq packages and papers.
- lazappi's Single-cell Software table - Table of single cell software and it's functions. Live version here.
single-cell RNA-seq 工具大全的更多相关文章
- Advances in Single Cell Genomics to Study Brain Cell Types | 会议概览
单细胞在脑科学方面的应用 Session 1: Deciphering the Cellular Landscape of the Brain Using Single Cell Transcript ...
- CAR-T|Single cell plan|Extracellular RNA|
生物医疗大数据 安吉丽娜朱莉发现抑癌基因事件,BRCA突变与乳腺癌关联. 个体化测序商品23 and me 多组学数据研究:eg:太空和地球双胞胎发现生化指标差不多. 研究模式和工业模式相结合. 研究 ...
- 单细胞参考文献 single cell
许多分析软件 : https://github.com/seandavi/awesome-single-cell#software-packages Smart-seq.CEL-seq.SCRB-se ...
- 单细胞测序技术(single cell sequencing)
单细胞测序技术(single cell sequencing) 2018-03-02 11:02 来源: 一呼百诺 点击次数:6587关键词: 前言 单细胞生物学最近几年是非常热门的研究方向 ...
- Analysis of single cell RNA-seq data(单细胞终极课程)
业界良心啊,开源的单细胞课程. 随便看了几章,课程写得非常用心,非常适合新手. 课程地址:Analysis of single cell RNA-seq data 源码地址:hemberg-lab/s ...
- Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing
Title: Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing 课题的目的 ...
- RNA seq 两种计算基因表达量方法
两种RNA seq的基因表达量计算方法: 1. RPKM:http://www.plob.org/2011/10/24/294.html 2. RSEM:这个是TCGAdata中使用的.RSEM据说比 ...
- RNA -seq
RNA -seq RNA-seq目的.用处::可以帮助我们了解,各种比较条件下,所有基因的表达情况的差异. 比如:正常组织和肿瘤组织的之间的差异:检测药物治疗前后,基因表达的差异:检测发育过程中,不同 ...
- mongoDB GUI客户端工具大全
网易blog - MongoDB GUI客户端工具大全 oschina - MonjaDB 1.0.2 发布,MongoDB 的 GUI 客户端 oschina创建人红薯对MonjaDB官方文 ...
随机推荐
- 【 记忆网络 2 】 End-to-End Memory Network
继上一篇:Memory Network 1. 摘要 引入了一个神经网络,在一个可能很大的外部记忆上建立了一个recurrent attention模型. 该体系结构是记忆网络的一种形式,但与该工作中的 ...
- index read-only
系统重启后,Eleastisearch6.5.0在给 Eleastisearch 更新索引的时候报了一个错误:ClusterBlockException[blocked by: [FORBIDDEN/ ...
- 安装GDB-ImageWatch ,在QT中查看图像
GDB_ImageWatch是在Linux下基于QT编写图像处理程序的调试程序. 由于并非像ImageWatch一样由官方提供,而是在github上以代码的方式进行提供,我们在使用的时候需要自己编译, ...
- 通过WireShark抓取iPhone联网数据方法
通过WireShark抓取iPhone联网数据方法 命令行 rvictl -s <UDID> 然后再wireshark选择rvi0进行抓包即可 抓包完后,移除用命令 rvictl -x & ...
- 关于变量,JAVA基本数据类型,运算符类型,如何从控制台接收输入的数据
一,变量与变量的使用 1.变量是在程序运行中其值可以改变的量,java程序的一个基本存储单元 2.变量的使用 变量类型+变量名 二,JAVA基本数据类型 1.数值型a.整点类型(byte.short. ...
- 如何在基于Bytom开发过程中集成IPFS
本文介绍了基于Bytom开发过程中集成IPFS. step1: 搭建bytom节点 比原相关资料:https://github.com/Bytom-Community/Bytom_Docs 搭建byt ...
- WEB 前端插件整理
Vs Code 系统插件 #1 Bracket Pair Colorizer 让括号拥有独立的颜色,易于区分.可以配合任意主题使用. #2 Code Runner 非常强大的一款插件,能够运行多种语言 ...
- 函数func_get_args详解
func_get_args ------获取一个函数的所有参数 function foo() { $numargs = func_num_args(); //参数数量 echo "参数个数是 ...
- ckeditor5 增加居中alignment
https://ckeditor.com/docs/ckeditor5/latest/builds/guides/integration/installing-plugins.html 克隆下来 gi ...
- css js 兼容问题
js 兼容问题 1. document.form.item 问题问题:代码中存在 document.formName.item("itemName") 这样的语句,不能在FF下运 ...