文章在这:Tumor microenvironment remodeling after neoadjuvant immunotherapy in non-small cell lung cancer revealed by single-cell RNA sequencing 方法:来自3名治疗前和12名接受新辅助PD-1阻断联合化疗的非小细胞肺癌(NSCLC)患者的~92,000个单细胞的转录组。根据病理反应将12个治疗后样本分为两组:MPR(n = 4)...
Peng等人.54的单细胞RNA测序数据,基因组序列归档(https://ngdc.cncb.ac.cn/gsa/),访问号PRJCA001063; Raghavan等人.41的单细胞RNA测序数据,单细胞门户(https://singlecell.broadinstitute.org),访问号SCP1644; PanCuRx的bulk RNA测序数据45,欧洲基因表型档案(https://ega-archive.org),访问号EGAS00001002543; ...
本次演示使用的数据来自2017年发表于Cell的头颈鳞癌单细胞文章:Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Head and Neck Cancer。本次演示提供处理好的测试数据,以及所有代码,一共6个脚本(我目前写得最详细的教程,也是全网少有的)。 数据的预处理就不演示了,... ...
Fixed all print statements python 3.x+ error, fixed print statement b… Feb 6, 2020 preprocessing.sh Update preprocessing.sh Aug 11, 2018 README coupledNMF Introduction Here is the source code for Integrative analysis of single cell genomics data by coupled nonnegative matrix factorizations. When...
Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R, and GenePattern Notebook implementations of CoGAPS. bioRxiv (2022) doi:10.1101/2022.07.09.499398. Fertig, Elana J., Jie Ding, Alexander V. Favorov, Giovanni Parmigiani, and ...
Resolving single-cell heterogeneity from hundreds of thousands of cells through sequential hybrid clustering and NMF 论文摘要 单细胞RNA测序(scRNA-Seq)技术的快速发展,开发了多种计算模型,以检测转录一致性的算法。虽然检测异构性的算法的复杂性有所增加,但大多数算法需要用户调试,严重依赖于降维技术,并且不能扩展...
本教程演示了如何使用mixscape 分析 single-cell pooled CRSIPR screens。我们介绍新的seurat功能: 生信技能树jimmy 2022/01/10 6150 实战出真知——单细胞基础流程 https网络安全数据分析go 我们选择的数据已经发表的文章题目是“Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage popu...
JSNMFuP: A unsupervised method for the integrative analysis of single-cell multi-omics data based on non-negative matrix factorization. This is the Python implementation of the JSNMFuP algorithm. Note that this implementation supports GPU acceleration. 1. Installation You can use the following comma...
Python is gaining popularity in single-cell data analysis. Two examples are scanpy (for scRNA-seq) and episcanpy (for single cell epigenomic data, e.g., scATAC-seq). To ensurescopenis usable in this context, we provide ajupyter notebookto show you how to combine scOpen and (epi)scanpy ...
Since the Cell Ranger (https://github.com/10XGenomics/cellranger) is one of the most popular single cell preprocessing software, our algorithm can further process the output of Cell Ranger. For example, one of the Cell Ranger output is the matrix.mtx as ...