https://www.jianshu.com/p/9bba0214844b sce构建的是一个SingleCellExperiment对象 核心分为4块: 1、assay:核心部分(盖了几层楼):表达矩阵部分 2、colData:sample/cell annotation:meta信息样本注释部分,细胞相关信息 3、rowData:feature annotation:基因信息 4、reducedDims:PCA,tSNE,uMAP等细胞降维聚类信息,降维...
adata=sc.read(filename)# 加入数据 anno=pd.read_csv(filename_sample_annotation)# 加入样本分组信息 adata.obs['cell_groups']=anno['cell_groups']# categorical annotationoftype pandas.Categorical # 加入时间信息 adata.obs['time']=anno['time']# numerical annotationoftype float # 甚至可以直接赋值 ...
slack:https://join.slack.com/t/omicsml/shared_invite/zt-1hxdz7op3-E5K~EwWF1xDvhGZFrB9AbA 我们欢迎对deep learning in single cell analysis感兴趣的童鞋一起构建DANCE:A Deep Learning Library and Benchmark for Single-Cell Analysis整个社区,以推动整个社区的建设和发展。
https://cf.10xgenomics.com/samples/cell/pbmc3k/pbmc3k_filtered_gene_bc_matrices.tar.gz 代码参考自scanpy的标准流程: https://scanpy.readthedocs.io/en/stable/tutorials/basics/clustering-2017.html https://scanpy.readthedocs.io/en/stable/tutorials/basics/clustering.html#manual-cell-type-annotation impor...
Here we introduce the usage of celltype package. The main function uses adictionary of immune cell markershat consist on expression level measurements of genes in different immune cell types. We use this dictionary to predict the likely cell type of a experimental dataset of single cell transcript...
SCANPY: large-scale single-cell gene expression data analysis F. Alexander Wolf, Philipp Angerer, Fabian J. Theis Genome Biology2018 Feb 06. doi:10.1186/s13059-017-1382-0. You can cite the scverse publication as follows: The scverse project provides a computational ecosystem for single-cell...
single-cell cell-type-classification cell-annotation cell-typing Resources Readme License MIT license Activity Custom properties Stars 14 stars Watchers 3 watching Forks 9 forks Report repository Releases No releases published Packages No packages published Contributors 7 Languages Python ...
SCENIC(single-cell regulatory network inference and clustering)是一个基于共表达和motif分析,计算单细胞转录组数据基因调控网络重建以及细胞状态鉴定的方法。在输入单细胞基因表达量矩阵后,SCENIC经过以下三个步骤完成转录因子分析: 第一步,GENIE3(随机森林)/GRNBoost (Gradient Boosting) 推断转录因子与候选靶基因之间...
adata.obs['cell type'] = adata.obs['louvain'].map(cluster2annotation).astype('category') 根据作者文中提到的一些marker 和 cellmarker ,PanglaoDB 数据库进行注释!这两个数据库是我经常光顾的。。原因就是简单!!! marker_genes_dict = { 'cancercells': ['KRT19'], ...
RCA:https://github.com/prabhakarlab/RCAv2RCA(Reference Component Analysis) is a computational approach for robust cell type annotation of single cell RNA sequencing data (scRNAseq). It is developed by the Prabhakar lab at the Genome Institute of Singapore (GIS). The original version of RCA is...