Fig_k.Rmd

---
title: "Data Visualization"
output: html_notebook
---

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#Download dataset
```{r}
data <- read.csv("/Users/sanzidaakhteranee/Documents/HackBio_Contest/figure_one_k.csv", header= TRUE, sep = ",")
print(data)
```


#Remove column
```{r}
data <-subset (data, select = -X)
print(data)
```


#Divide a data vector into groups as defined by technology
```{r}
partitions <- split(data, data$tech)
print(partitions)
```


Create dataframe or matrix for technology
```{r}
technology <- unique(data$tech)
technology
```


#Plotting boxplot
```{r}
par(mfrow=c(2,5))
par(mar=c(5,4,4,2)+0.1)

boxplot(seurat_cell_type_pred_score ~ sample_id, 
        data=partitions$ddseq, 
        col= 'cornflowerblue', pch=19, 
        xlim =c(), ylim=c(0.0, 1.0), 
        xaxt ='n', main='ddseq', 
        xlab= 'sample_id', ylab= 'Seurat Score')

boxplot(seurat_cell_type_pred_score ~ sample_id, 
        data=partitions$mtscatacfacs, col= 'darkorange', pch=19, 
        xlim =c(), ylim=c(0.0, 1.0), 
        xaxt ='n', main='mtscatacfacs', 
        xlab= 'sample_id', ylab= 'Seurat Score')

boxplot(seurat_cell_type_pred_score ~ sample_id, 
        data=partitions$ '10xmultiome', col= 'darkgreen', pch=19, 
        xlim =c(), ylim=c(0.0, 1.0), 
        xaxt ='n', main='10xmultiome', 
        xlab= 'sample_id', ylab= 'Seurat Score')


boxplot(seurat_cell_type_pred_score ~ sample_id, 
        data=partitions$'10xv11', col= 'deeppink', pch=19, 
        xlim =c(), ylim=c(0.0, 1.0), 
        xaxt ='n', main='10xv11', 
        xlab= 'sample_id', ylab= 'Seurat Score')

boxplot(seurat_cell_type_pred_score ~ sample_id, 
        data=partitions$'10xv11c', col= 'darkorchid', pch=19, 
        xlim =c(), ylim=c(0.0, 1.0), 
        xaxt ='n', main='10xv11c', 
        xlab= 'sample_id', ylab= 'Seurat Score')

boxplot(seurat_cell_type_pred_score ~ sample_id, 
        data=partitions$'10xv2', col= 'aquamarine4', pch=19, 
        ylim=c(0.0, 1.0), 
        xaxt ='n', main='10xv2', 
        xlab= 'sample_id', ylab= 'Seurat Score')

boxplot(seurat_cell_type_pred_score ~ sample_id, 
        data=partitions$hydrop, col= 'blue4', pch=19, 
        xlim =c(), ylim=c(0.0, 1.0), 
        xaxt ='n', main='hydrop', 
        xlab= 'sample_id', ylab= 'Seurat Score')

boxplot(seurat_cell_type_pred_score ~ sample_id, 
        data=partitions$mtscatac, col= 'darkmagenta', pch=19, 
        xlim =c(), ylim=c(0.0, 1.0), 
        xaxt ='n', main='mtscatac', 
        xlab= 'sample_id', ylab= 'Seurat Score')

boxplot(seurat_cell_type_pred_score ~ sample_id, 
        data=partitions$'s3atac', col= 'azure4', pch=19, 
        xlim =c(), ylim=c(0.0, 1.0), 
        xaxt ='n', main='s3tac', 
        xlab= 'sample_id', ylab= 'Seurat Score')

boxplot(seurat_cell_type_pred_score ~ sample_id, 
        data=partitions$'10xv1', col= 'coral2', pch=19, 
        xlim =c(), ylim=c(0.0, 1.0), 
        xaxt ='n', main='10xv1', 
        xlab= 'sample_id', ylab= 'Seurat Score')
```