一张图总结一下CellMarker 2.0数据库概况:👇 3CellMarker 2.0 更新亮点 本次更新的亮点如下:👇 新增36300个tissue-cell type-marker条目、474个组织、1901个细胞类型和4566个marker; 新增48种测序技术分类的细胞marker,包括10×Chromium、Smart-seq2和Drop-seq等; 新增29种
The built-in cell type marker database was used as the reference for all ScType annotations. Manually annotated cell types were treated as cell clusters and given as inputs to ScType. ScType directly generates cluster-level cell type annotations. CellMarker2.0 CellMarker2.0 (ref. 13) only ...
大家可以通过选择物种、组织和输入基因来定义细胞类型,这里我们以人类的血液为例,heatmap显示输入的基因出现在哪些细胞类型的marker中,以及这些细胞类型的得分。🥳 2️⃣ 这个Score的计算是这样得来的:👇 CellTypeScorei=AB Note !其中A代表输入基因与细胞类型i中Marker基因的交集数,B代表细胞类型i中Marker基因...
We annotated cell clusters based on the expression of curated known cell markers. The above cell markers with cell types were selected from Cell Markers and CellTypist database83,84 and these selected marker genes in the annotated clusters have log2...
5. data(example_marker_mat) # 计算细胞标准化因子(示例数据已经包含该部分信息,如果是新数据,需要重新计算。推荐使用scran包中的computeSumFactors 函数。注意:在计算标准化因子之前最好不要对表达矩阵的基因进行筛选 6. # example_sce <- computeSumFactors(sce) ...
We curated a comprehensive cell marker database named scMayoMapDatabase and developed a companion R package scMayoMap, an easy-to-use single-cell annotation tool, to provide fast and accurate cell type annotation. The effectiveness of scMayoMap was demonstrated in 48 independent scRNA-seq dataset...
http://localhost:17435/notebooks/shared_dataset/zhixin/2023_Hickey_Snyder_human_Intestine_Nature/data_preparation.ipynb#cell-type-find-mapping 我称之为fine mapping 用一个旧model(旧marker)来预测一个新数据,大概率会有错误预测的部分。 我们可以根据预测来重新鉴定新marker,基于此marker来用新数据预测新数据...
Predict the celltype of a cluster from Seurat FindMarker data scrna-seq marker-genes celltype seurat Updated Sep 24, 2024 Python proteomicsyates / pctsea-parent Star 0 Code Issues Pull requests PCTSEA (Proteomics Cell Type Enrichment Analysis) is a tool designed to statistically determine...
rcellmarkerprovides method to identify cell type based on single cell sequencing data. Since most methods try to annotate cell types manually after clustering the single-cell RNA-seq data. Such methods are labor-intensive and heavily rely on user expertise, which may lead to inconsistent results....
Fig. 1: Cell-type-specific transcriptomic aging clocks for neurogenic regions. a, Training data for single-cell transcriptomic aging clocks. 10x Genomics single-cell transcriptomics on SVZ neurogenic regions from four independent cohorts of 4–8 male mice, aged 3.3 to 29 months (Supplementary Table...