sex_metadata.Rmd

---
title: "sex_metadata"
output: html_document
---

# create new "sex_all" column
```{r}
dataset21and22$sex_all <- NA
dataset21and22$sex_all <- as.character(dataset21and22$sex_all)
```


# merge columns for "host sex" and "sex" to "sex_all" column
```{r}

# iterate by row
# damn this is slow...
column_name <- "sex"

for (n_row in 1:nrow(dataset21and22)) {
  # check that value exists for "host sex"
  if (!is.na(dataset21and22[n_row,column_name])) {
    if (dataset21and22[n_row,column_name] != "pooled male and female") {
      dataset21and22[n_row, "sex_all"] <- dataset21and22[n_row, column_name]
    }
  }
}

sum(!is.na(dataset21and22$sex_all))

```

# visualization of sex for SRM present group
``` {r}
ggplot(data = subset(dataset21and22, !is.na(dataset21and22$sex_all)), aes(x = sex_all, fill = SRM_present)) +
  geom_bar() +
  xlab("sex") +
  ggtitle("Number of Samples by Sex") +
  geom_text(stat='count', aes(label=..count..), vjust=-0.5, color="black")

ggplot(data = subset(dataset21and22, !is.na(dataset21and22$sex_all)), aes(x = SRM_present, fill = sex_all)) +
  geom_bar(position = "fill") +
  ggtitle("Proportion of male and female samples by SRM Presence")

# RESULT: no significant difference in sex bewteen SRM present or absent groups
```