WebFeb 18, 2024 · 在初始化函数中,我们创建了一个 LSTM 层,并将其封装在 `self.lstm` 中,然后再创建一个全连接层,并将其封装在 `self.fc` 中。 在前向传播函数中,我们首先初始化隐藏状态和细胞状态,然后通过 `self.lstm` 层对输入进行计算,最后通过 `self.fc` 层对计算结果 … read10xCounts: Load data from a 10X Genomics experiment; read10xMolInfo: Read the 10X molecule information file; reexports: Objects exported from other packages; removeAmbience: Remove the ambient profile; swappedDrops: Clean barcode-swapped droplet data; write10xCounts: Write count data in the … See more This function has a long and storied past.It was originally developed as the read10xResults function in scater, inspired by the Read10X … See more Zheng GX, Terry JM, Belgrader P, and others (2024).Massively parallel digital transcriptional profiling of single cells. Nat Commun8:14049. … See more A SingleCellExperiment object containing count data for each gene (row) and cell (column) across all samples. 1. Row metadata will contain the fields "ID" and "Symbol".The former … See more splitAltExps, to split alternative feature sets (e.g., antibody tags) into their own Experiments. write10xCounts, to create 10X-formatted file(s) … See more
Utilities for handling droplet-based single-cell RNA-seq data
WebScaleData()函数将基因的表达转换为Z分数(值以 0 为中心,方差为 1)。 它存储在 seurat_obj[['RNA']]@scale.data,用于下游的PCA降维。 默认是仅在高可变基因上运行标 … Web此时,我们需要再安装spatstat.data这个包: > install.packages('spatstat.data') 当安装spatstat.data包时,可能还会出现spatstat.utils和spatstat.data版本不适配的问题,导致spatstat.data无法正确被安装。 安装时报错信息: Error: package or namespace load failed for ‘Seurat’ in loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i ... dynamical systems analysis of coordination
write10xCounts : Write count data in the 10x format
Web3.4.2 From Cellranger output. For 10X Genomics data, the Cellranger software suite will produce an output directory containing counts and feature/barcode annotations. We can read this into R by supplying the directory path to read10xCounts() from the DropletUtils package, as demonstrated below using a 4000 peripheral blood mononuclear cell … WebScaleData()函数将基因的表达转换为Z分数(值以 0 为中心,方差为 1)。 它存储在 seurat_obj[['RNA']]@scale.data,用于下游的PCA降维。 默认是仅在高可变基因上运行标准化。 combined.data <- ScaleData(combined.data) 最开始分析单细胞的时候,这里有点疑惑。 Webseurat涉及的数据分析包括很多步骤。 之前只顾着干活儿,也没有系统的整理过分析中的具体内容。 这里就参照网上大神们分享的帖子,来梳理一下。 dynamical systems and linear algebra