phylogenetics.Rmd

# Phylogenetic data

[@Rambaut2020Nov]

[@Singer2020Jun]


```{r message=FALSE}
library(sars2pack)
library(ggplot2)
library(dplyr)
library(ggtree)
library(ape)
library(stringr)
```

```{r message=FALSE}
ntr = cov_glue_newick_data()
```


see See Figure \@ref(fig:ggtreeNewick)


```{r ggtreeNewick,out.width='100%',fig.width=12,fig.height=12,fig.cap='abc'}
groups = str_match(ntr$tip.label,'.*_([A-Z][\\.]?[0-9]?[0-9]?).*')
ntr = groupOTU(ntr, split(ntr$tip.label,groups[,2]))
ggtree(ntr, aes(color=group), layout="circular", branch.length="none") +
  geom_tiplab(size=3, aes(angle=angle)) +
  ggtitle('COVID Glue Phylogenetic Clades')
```

```{r warning=FALSE}
dat = cov_glue_lineage_data()
dat = dat %>%
    dplyr::mutate(lineage = sub('^([^.][.]?[^.]+).*', '\\1', lineage)) %>%
    dplyr::mutate(region = countrycode::countrycode(country,origin='country.name',
                                                    destination='region')) %>%
    dplyr::group_by(epiweek,lineage,region) %>% 
    dplyr::summarize(cases=n()) %>%
    dplyr::filter(!is.na(region)) %>%
    dplyr::ungroup()
head(dat)
```

```{r lineageSpread,fig.height=12,fig.width=10,out.width='100%', warning=FALSE}
p = dat %>%
    ggplot(aes(x=epiweek,y=cases,fill=lineage)) +
    geom_bar(stat='identity', position='fill') +
    facet_wrap("region",ncol=2) +
    theme(legend.position='bottom')
p
```

## Notes

- https://nextstrain.org/help/general/how-to-read-a-tree