https://github.com/mrc-ide/skygrowth

Phylodynamic inference
https://github.com/mrc-ide/skygrowth

Last synced: about 2 months ago
JSON representation

Phylodynamic inference

• Host: GitHub
• URL: https://github.com/mrc-ide/skygrowth
• Owner: mrc-ide
• License: mit
• Created: 2017-08-29T14:46:26.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2020-05-15T19:35:43.000Z (over 4 years ago)
• Last Synced: 2023-10-26T07:08:43.934Z (about 1 year ago)
• Language: R
• Homepage:
• Size: 508 KB
• Stars: 12
• Watchers: 5
• Forks: 4
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# skygrowth

[Phylodynamic inference](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002947)  of effective population size for time-scaled phylogenies. Inference makes use of Bayesian Gibbs-within-Metropolis MCMC and fast maximum a posteriori algorithms. The growth rate of effective population size is modeled as a simple Brownian motion process. 

This package includes functions for

* incorporating time-varying covariates into phylodynamic inference. This is appropriate if the covariate is expected to alter the growth rate of effective population size

* computing the reproduction number (expected number of offspring) through time given prior information about the generation interval

## To cite

Erik Volz and Xavier Didelot, [Modeling the growth and decline of pathogen effective population size provides insight into epidemic dynamics and drivers of antimicrobial resistance](https://doi.org/10.1093/sysbio/syy007), Systematic Biology, 2018

## H3N2 influenza in New York

This data set is provided in the phylodyn R package by Karcher et al. 

It is based on 12 consecutive seasonal influenza seasons in NY state up to 2004. 

```r

require(skygrowth)

require(ape)

require(ggplot2)

load(system.file( 'NY_flu.rda', package='skygrowth')  )

(tr <- NY_flu) # NOTE branch lengths in weeks  / 13 years in all

```

```

## 

## Phylogenetic tree with 709 tips and 708 internal nodes.

## 

## Tip labels:

## 	CY000001date568.3, CY000009date563.9, CY000017date565.7, CY000025date565.3, CY000033date571.0, CY000041date565.9, ...

## 

## Rooted; includes branch lengths.

```

```r

fit <- skygrowth.map( tr 

 , res = 24*13  # Ne changes every 2 weeks

 , tau0 = .1    # Smoothing parameter. If prior is not specified, this will also set the scale of the prior

)

```

```r

plot( fit ) 

```

![plot of chunk unnamed-chunk-1](figure/unnamed-chunk-1-1.png)

We can compare this to the standard skyride model: 

```r

require(phylodyn)

```

```r

b0 <- BNPR( tr )

plot_BNPR( b0 )

```

![plot of chunk unnamed-chunk-2](figure/unnamed-chunk-2-1.png)

We can also run the slower MCMC version which should provide more accurate CIs:

```r

mcmcfit <- skygrowth.mcmc( tr, res = 24*13, tau0=.1 )

plot( mcmcfit )  + scale_y_log10(limits=c(.01, 1e5))

```

![](figure/nyflu_mcmcfit2.png)

And we can visualise the growth rate through time:

```r

growth.plot( mcmcfit )

```

![](figure/nyflu_growth2.png)