# single_cell

**Repository Path**: mo_xinwu/single_cell

## Basic Information

- **Project Name**: single_cell
- **Description**: 单细胞相关
- **Primary Language**: R
- **License**: GPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2023-03-20
- **Last Updated**: 2024-10-10

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# README
## 仓库用途
主要用于存放一些单细胞相关的 code 
## function
1. 用于 tsne 和 umap 图美化 -> tsne_umap_beautif.R
<img src='http://xinwu-markdown.obs.cn-east-3.myhuaweicloud.com/xinwu-img/tsne_umap_beautif_3.png'>

2. 用于获取 barcode 的原始信息，并添加 线粒体基因占比、核糖体基因占比、红细胞基因占比信息：Seurat_get_barcode_info.R

3. 添加 plot_gene_dot 函数，用于在 tsne 或 umap 图上展示表达某个基因的细胞 -> tsne_umap_beautif.R
<img src='http://xinwu-markdown.obs.cn-east-3.myhuaweicloud.com/xinwu-img/Genergy_work/tsne_umap_add_gene_expr.png'>

4. get_gene_set.R 获取基因集数据 <br/>
    在进行 GSVA 或 GSEA 分析前，我们需要得到基因集数据，常用的基因集数据有 C1、C2、...、C8、H 9个数据集，可以通过 msigdbr R packages 来获取不同物种的不同数据集。
    <img src='http://xinwu-markdown.obs.cn-east-3.myhuaweicloud.com/xinwu-img/Genergy_work/Gene_set.jpeg'>
- 可用的 Species

| species_name                    | species_common_name                                          |
| ------------------------------- | ------------------------------------------------------------ |
| Anolis carolinensis             | Carolina anole, green anole                                  |
| Bos taurus                      | bovine, cattle, cow, dairy cow, domestic cattle, domestic cow, ox, oxen |
| Caenorhabditis elegans          | NA                                                           |
| Canis lupus familiaris          | dog, dogs                                                    |
| Danio rerio                     | leopard danio, zebra danio, zebra fish, zebrafish            |
| Drosophila melanogaster         | fruit fly                                                    |
| Equus caballus                  | domestic horse, equine, horse                                |
| Felis catus                     | cat, cats, domestic cat                                      |
| Gallus gallus                   | bantam, chicken, chickens, Gallus domesticus                 |
| Homo sapiens                    | human                                                        |
| Macaca mulatta                  | rhesus macaque, rhesus macaques, Rhesus monkey, rhesus monkeys |
| Monodelphis domestica           | gray short-tailed opossum                                    |
| Mus musculus                    | house mouse, mouse                                           |
| Ornithorhynchus anatinus        | duck-billed platypus, duckbill platypus, platypus            |
| Pan troglodytes                 | chimpanzee                                                   |
| Rattus norvegicus               | brown rat, Norway rat, rat, rats                             |
| Saccharomyces cerevisiae        | baker's yeast, brewer's yeast, S. cerevisiae                 |
| Schizosaccharomyces pombe 972h- | NA                                                           |
| Sus scrofa                      | pig, pigs, swine, wild boar                                  |
| Xenopus tropicalis              | tropical clawed frog, western clawed frog                    |

5. 双细胞预测: run_scrublet.py <br/>
参数说明：<br/>--gene_cell_matrix_input_file: 输入的 gene x cell矩阵文件行为基因, 列为细胞<br/>
--expected_doublet_rate：预估的双细胞率, 默认0.06<br/>
--predicted_output_file：结果输出文件, `predicted_doublets` 列为1的即为双细胞，应去除。<br/>

|Barcode           |doublet_scores      |predicted_doublets|
|------------------|--------------------|------------------|
|AAACCCACAAGGCGTA-1|0.04035002430724357 |0                 |
|AAACCCACATGGGATG-1|0.031759656652360524|0                 |
|AAACCCAGTACTCCGG-1|0.09191277946453216 |0                 |
|AAACCCACAGCAGATG-1|0.31719128329297813 |1                 |
|AAAGAACAGCTGTACT-1|0.27234342012667123 |1                 |
|AAAGTCCAGCTCCACG-1|0.46285714285714286 |1                 |

6. legend 为圆圈数字
在 `tsne_umap_beautif.R` 添加 `plot_number_circle` 用于绘制 legend 为圆圈数字, 注意：
- 需要对圆圈进行修大小修改 可以修改 `draw_number_circle`
- 只能用于绘制 一个 cluster 对应 一个 CellType 的情况 
- 一定要注意的是 CellType 一定要记得将其转成 factor, 注意顺序, 一定要将 CellType 的 factor 顺序要和 Cluster 的顺序要对对应
```R
data <- data.table::fread("demo_tsne_umap.txt") %>% filter(Cluster %in% c(1,2,3,4,5))
data$CellType <- NA
data$CellType[data$Cluster == "1"] <- "Th2"
data$CellType[data$Cluster == "2"] <- "ILC1"
data$CellType[data$Cluster == "3"] <- "DC2"
data$CellType[data$Cluster == "4"] <- "Tc1"
data$CellType[data$Cluster == "5"] <- "Treg"
data$CellType <- factor(data$CellType,levels = unique(data$CellType)[order(unique(data$Cluster))])

p1 <- plot_number_circle(reduction_data = data,colors_by = "CellType",
               labels_by = "Cluster",show_labels = T,
               point_size = 1,adjust_axis = T,
               label_size = 5)

data[,c(2,3)] <- NULL
p2 <- plot_number_circle(reduction_data = data,colors_by = "CellType",
          labels_by = "Cluster",show_labels = T,
          point_size = 1,adjust_axis = T,
          label_size = 5)
p <- p1 | p2
```
<img src='http://xinwu-markdown.obs.cn-east-3.myhuaweicloud.com/xinwu-img/Genergy_work/tsne_umap_beautif_number_circle.png'>