norm.200.m100.sd1.vs.m200.sd1.list: A list of simulated datasets.

In mi4p: Multiple Imputation for Proteomics

A list of simulated datasets.

Description

This list of 100 datasets was simulated using the default values of the options of the protdatasim function and the set.seed value set to 4619.

Format

The format is: List of 100 data.frames.

data.frame

200 obs. of 11 variables

id.obs

int [1:200] 1 2 3 4 5 6 7 8 9 10 ...

X1

num [1:200] 99.6 99.9 100.2 99.8 100.4 ...

X2

num [1:200] 97.4 101.3 100.3 100.2 101.7 ...

X3

num [1:200] 100.3 100.9 99.1 101.2 100.6 ...

X4

num [1:200] 99.4 99.2 98.5 99.1 99.5 ...

X5

num [1:200] 98.5 99.7 100 100.2 100.7 ...

X6

num [1:200] 200 199 199 200 199 ...

X7

num [1:200] 200 200 202 199 199 ...

X8

num [1:200] 202 199 200 199 201 ...

X9

num [1:200] 200 200 199 201 200 ...

X10

num [1:200] 200 198 200 201 199 ...

attr(*, "metadata")

'data.frame': 10 obs. of 3 variables:

Sample.name

chr [1:10] "X1" "X2" "X3" "X4" ...

Condition

Factor w/ 2 levels "A","B": 1 1 1 1 1 2 2 2 2 2

Bio.Rep

int [1:10] 1 2 3 4 5 6 7 8 9 10

...

...

Author(s)

M. Chion, Ch. Carapito and F. Bertrand.

Source

We simulated the data.

References

M. Chion, Ch. Carapito and F. Bertrand (2021). Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics. arxiv:2108.07086. https://arxiv.org/abs/2108.07086.

Examples

data(norm.200.m100.sd1.vs.m200.sd1.list)
str(norm.200.m100.sd1.vs.m200.sd1.list)

mi4p documentation built on March 31, 2023, 6:23 p.m.