03-Network.Rmd

```{r}
my_packages <- c("tidyverse", "data.table",
                 "clusterProfiler", "org.Hs.eg.db")
pacman::p_load(char = my_packages)

tmp <- list()
```

# Prepare
```{r}
target_df4 <- readRDS(file = "Output/01/target_df4.Rds")
```

```{r}
herb_df <- data.frame(
  tcm = "Shen Ling Bai Zhu San",
  herb = unique(target_df4$herb)
)

compound_df <- target_df4[,c("herb", "molecule_name")] %>% unique()

target_df <- target_df4[,c("molecule_name", "GeneNames")] %>% unique()
```

```{r}
ID_df <- data.frame(
  "Source" = c(herb_df$tcm, compound_df$herb, target_df$molecule_name),
  "Target" = c(herb_df$herb, compound_df$molecule_name, target_df$GeneNames)
)
```

Type dataframe:
```{r}
anno_df <- data.frame(
  term = c("Shen Ling Bai Zhu San", unique(herb_df$herb),
           unique(compound_df$molecule_name),
           unique(target_df$GeneNames)),
  type = c("formula", rep("herb", length(unique(herb_df$herb))),
           rep("compound", length(unique(compound_df$molecule_name))),
           rep("target", length(unique(target_df$GeneNames)))
           )
)
```

```{r}
table(anno_df$type)
```

csv may induce column error.

```{r}
# fwrite(ID_df, file = "Output/03/ID_df.csv", quote = T)
# fwrite(anno_df, file = "Output/03/anno_df.csv")

writexl::write_xlsx(ID_df, path = "Output/03/ID_df.xlsx")
writexl::write_xlsx(anno_df, path = "Output/03/anno_df.xlsx")
```

See: `operation_cytoscape.md`

# PPI
```{r}
fwrite(data.frame("x" =unique(target_df$GeneNames)), col.names = F, file = "Output/03/ppi_input.txt")
```

```{r}
tsv <-  read.table("Input/String/string_interactions_short.tsv", comment.char = "!",header = T)
tsv2 <-  tsv[,c(1,2,ncol(tsv))]
head(tsv2)
write.table(tsv2,
            file = "Output/03/ppi_cyto.txt",
            sep = "\t",
            quote = F,
            row.names = F)
```

```{r}
ppi_top <- fread("Input/String/degree.csv")
```

# Enrichment
```{r}
marker <- bitr(ppi_top$Name, OrgDb = "org.Hs.eg.db", 
                   fromType = "SYMBOL", toType = "ENTREZID")
```

```{r}
KEGG <- enrichKEGG(gene = marker$ENTREZID,
                      organism     = 'hsa',
                      pvalueCutoff = 0.05,
                      qvalueCutoff =0.05)
KEGG_df <- KEGG@result
```

```{r}
vec_toll <- strsplit("207/7124/3569/841", "/")[[1]]

toll_df <- marker[marker$ENTREZID %in% vec_toll,]
toll_df
```

```{r}
cat(toll_df$SYMBOL, sep = "，")
```

# Select compounds
```{r}
target_df5 <- target_df4[target_df4$GeneNames %in% toll_df$SYMBOL,]

table(target_df5$herb)
```

```{r}
table(target_df5$molecule_name)
```


# Save