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Description

The age-specific survival analysis workflow gives the basic information on the mean, variance and coefficient of variation (cv) of the time spent in each stage class and the mean and variance of the time to death.

 Analyses:

 Fundamental matrix (N)

  • Variance (var)
  • Coefficient of variation (CV)
  • Meaneta
  • Vareta

Biovel Portal Tutorial

To run this workflow in the Biovel Portal please refer to Tutorial Manual

 

General

Name of the workflow and its myExperiment identifier

Name: Age specific survival analysis.

The workflow pack can be downloaded from myExperiment pack 631 or the workflow at: myExperiment workflow 3286

Date, version and licensing

Last updated: 24th July 2014

Version: 3

Licensing: CC-BY-SA

How to cite this workflow

To report work that has made use of this workflow, please add the following credit acknowledgement to your research publication:

The input data and results reported in this publication (tutorial) come from data (Dr. Gerard Oostermeijer unpublished results and publication: Oostermeijer, J.G.B. M.L. Brugman, E.R. de Boer; H.C.M. Den Nijs. 1996. Temporal and Spatial Variation in the Demography of Gentiana pneumonanthe, a Rare Perennial Herb. The Journal of Ecology, 84: 153-166.) using BioVeL workflows and services (www.biovel.eu). Age specific survival workflow was run on <date of the workflow run>. BioVeL is funded by the EU’s Seventh Framework Program, grant no. 283359.

 

Scientific specifications

Keywords

Matrix Population Models, Age specific survival, Fundamental matrix (N), Variance (var), Coefficient of variation (cv), Meaneta, Vareta.

Scientific workflow description

The age-specific survival analysis workflow gives the basic information on age-specific survival; this includes the mean, variance and coefficient of variation (CV) of the time spent in each stage class and the mean and variance of the time to death.

The aim of the age-specific survival analysis workflow is to provide a connected environment to calculate the mean, variance and coefficient of variation (CV) of the time spent in each stage class and the mean and variance of the time to death. The workflow accepts input data in a .txt format. The output is provided as a set of R results.

a) Fundamental matrix (N): is the mean of the time spent in each stage class.

b) Variance (var): is the variance in the amount of time spent in each stage class.

c) Coefficient of variation (CV): is the coefficient of variation of the time spent in each class (SD/mean- the ratio of the standard deviation to the mean).

d) Meaneta: is the mean of time to death, of life expectancy of each stage.

e) Vareta: is the variance of time to death.

 

Technical specifications

The Workflow requires a Taverna Engine. The simplest way to install a Taverna Engine is to install Taverna Workbench. The workflow also requires an Rserve installation with popbio package installed. It is possible to setup the workflow to use a remote Rserve. However, instructions for installing a local Rserve are provided below.

Dependencies

Install R software in your computer. See: http://www.r-project.org/

  • Start R, and install package Rserve:
    • install.packages(“Rserve”)
  • Install package popbio
    • install.packages(“popbio”)
  • Local R Server: (Rserve) running at port 6311. See https://wiki.biovel.eu/x/3ICD for additional information.

How it works

First, open R, once R is opened, type library(Rserve) and press enter; then type Rserve() and press enter again. You will see then something similar to the following message:


After this operation you can open Taverna and run the workflow.

 

Bibliography

This workflow was created using and based on Packages ‘popbio’ in R. (Stubben & Milligan 2007; Stubben, Milligan & Nantel 2011) and popdemo (Stott, Hodgson and Townley, 2013)

  • Caswell, H. 2001. Matrix population models: Construction, analysis and interpretation, 2nd Edition. Sinauer Associates, Sunderland, Massachusetts.
  • Jongejans E. & H. de Kroon. 2012. Matrix models. Chapter in Encyclopaedia of Theoretical Ecology (eds. Hastings A & Gross L) University of California, p415-423
  • Oostermeijer J.G.B., M.L. Brugman; E.R. de Boer; H.C.M. Den Nijs. 1996. Temporal and Spatial Variation in the Demography of Gentiana pneumonanthe, a Rare Perennial Herb. The Journal of Ecology, Vol. 84(2): 153-166.
  • Stott, I., D.J. Hodgson and S. Townley. 2013. popdemo: Provides Tools For Demographic Modelling Using Projection Matrices. Version 0.1-3.
  • Stubben, C & B. Milligan. 2007. Estimating and Analysing Demographic Models Using the popbio Package in R. Journal of Statistical Software 22 (11): 1-23
  • Stubben, C., B. Milligan, P. Nantel. 2011. Package ‘popbio’. Construction and analysis of matrix population models. Version 2.3.1
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