Dataset Open Access
Nettle, Daniel
Code and data for Nettle et al. 'Consequences of measurement error in qPCR telomere data: A simulation study'
Main simulation functions are contained in the script ‘simulation.functions.r’. When called, these functions (listed below) return datasets with requested properties containing both the ideal values of the quantities (Cqs, TS, etc.), and their post-error measured values. This allows the user to determine the differences between ideal and measured values, and perform other analyses. All simulation parameter values are user-specifiable. The script ‘paper.results.r’ reproduces all the figures and simulation results from the main paper. 'paper.results.r' also reads in the two .csv files of empirical data (dataset1 and dataset2).
Datasets consist of observations from n individuals. The steps common to all of the simulation functions are as follows:
The following functions are available. Specify desired parameter values in the parenthesis, e.g. generate.one.dataset(n=10000, error.telo=0.1, error.scg=0.1, error.cor=0). Default values in the simulation functions are generally those given in table 1 of the main paper.
Name | Size | |
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dataset1.csv
md5:e4b9d1dc9e3b4d569f26d057b08b8507 |
81.4 kB | Download |
dataset2.csv
md5:0d75626481beef56dbc4cc6e444ab679 |
2.1 kB | Download |
paper.results.r
md5:1b145c5d0d0f7f0fc8f8cd84489fc4b2 |
15.6 kB | Download |
simulation.functions.r
md5:e3a09a06957daf15b9457354c9a4f7da |
6.1 kB | Download |
All versions | This version | |
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Views | 126 | 58 |
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Data volume | 4.6 MB | 1.9 MB |
Unique views | 114 | 55 |
Unique downloads | 45 | 20 |