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https://github.com/biogenies/imputomics


https://github.com/biogenies/imputomics

amputation imputation metabolomics missing-values shiny webserver

Last synced: about 2 months ago
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README 

        
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output: github_document

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```{r setup, include=FALSE}

knitr::opts_chunk$set(echo = TRUE)

```



# imputomics 



*imputomics* is an R package and a shiny web server designed to simulate

and impute missing values. It offers 42 algorithms for imputing missing

values, especially in different types of ‘-omics’ data such as genomics,

transcriptomics, proteomics, and metabolomics. imputomics provides a

user-friendly interface that allows users to simulate missing values

based on different distributions and impute missing values using

state-of-the-art methods.



## Key Features:



1.  Imputation methods: imputomics offers the biggest collection of

    imputation methods for different types of omics data, including

    k-nearest neighbors (KNN), random forests, expectation-maximization

    (EM) algorithm, and principal components analysis (PCA) and many

    others.



2.  Performance evaluation: imputomics facilitates evaluating the

    performance of imputation methods. Users can evaluate imputation

    accuracy and compare different methods using metrics such as root

    mean squared error (RMSE), mean absolute error (MAE), and

    coefficient of determination (R-squared).



3.  Simulation of missing values: imputomics provides a variety of

    options for simulating missing values, including missing completely

    at random (MCAR), missing at random (MAR), and missing not at random

    (MNAR) mechanisms. Users can specify the percentage of missing

    values and the distribution from which the missing values are

    generated.

    



# Getting started



This repository contains the data and code necessary to reproduce the

results from the paper *imputomics: comprehensive missing data

imputation for metabolomics data*. It uses

[renv](https://CRAN.R-project.org/package=renv) package to assure the

reproducibility. As *imputomics* implements lots of missing value

imputations methods from other R packages.



## Webserver



The *imputomics* can be accessed through our [web

server](http://imputomics.umb.edu.pl/).



## Installation



*imputomics* is available on

[GitHub](https://github.com/BioGenies/imputomics)



To install *imputomics* you need to have *R* version >= 4.2.0.



``` r

devtools::install_github("BioGenies/imputomics")

```



Sometimes, not all packages can be installed on the first try. In this case, consider re-running the *install_github* function. 



### Docker



To enhance the reproducibility of *imputomics*, we share it also as a [rocker-based](https://github.com/rocker-org) container. The docker manifest is available in the *imputomics* repository: https://github.com/BioGenies/imputomics/blob/main/Dockerfile_imputomics.



## Reproducibility



To reproduce our environment you need to git clone our repo and activate renv.



``` bash 

git clone https://github.com/BioGenies/imputomics.git

```

``` r

renv::activate()

renv::restore()

```



### Troubleshooting



Q: I am receiving the following error message: "Error: HTTP error 403. API rate limit exceeded for [my IP]".

A: Due to its comprehensiveness, *imputomics* downloads many packages from GitHub, which may lead to exceeding the limit of GitHub API queries. 

Please consider setting the GitHub API token with usethis::create_github_token().



## Run imputomics



To run *imputomics* type the following command into an R console.



``` r

imputomics::imputomics_gui()

```



```{r echo = FALSE, results = 'asis'}

source(system.file("readme_scripts.R", package = "imputomics"))

cat(imputomics_citation())

cat(imputomics_contact())

cat(imputomics_funding())

cat(imputomics_funding_images())

```