| Title: | Unified Preprocessing Toolkit for Proteomics and Metabolomics |
|---|---|
| Description: | An integrated R package providing unified workflows for quality control, normalization, and visualization of proteomic and metabolomic data. The package simplifies preprocessing through automated imputation, scaling, and PCA-based exploratory analysis, enabling researchers to prepare omics datasets efficiently for downstream statistical and machine learning analyses. |
| Authors: | Isaac Osei [aut, cre], Dennis Opoku Boadu [aut], Chettupally Anil Carie [aut] |
| Maintainer: | Isaac Osei <[email protected]> |
| License: | GPL-3 |
| Version: | 0.1.0 |
| Built: | 2026-05-11 07:12:43 UTC |
| Source: | https://github.com/ikemillar/omicsprepr |
Exports processed omics data to a CSV file for downstream analysis.
export_clean(data, file_path)export_clean(data, file_path)
data |
A data frame containing the cleaned omics data. |
file_path |
A character string specifying the output file path. |
A message confirming export success.
## Not run: export_clean(my_cleaned_data, "output/cleaned_data.csv") ## End(Not run)## Not run: export_clean(my_cleaned_data, "output/cleaned_data.csv") ## End(Not run)
Impute Missing Values in Omics Data
impute_missing(data, method = c("mean", "median"))impute_missing(data, method = c("mean", "median"))
data |
Omics data frame with missing values. |
method |
Imputation method ("mean", "median"). |
Data frame with imputed values.
Integrate Proteomic and Metabolomic Data
integrate_omics(prot, met)integrate_omics(prot, met)
prot |
Proteomics data frame. |
met |
Metabolomics data frame. |
A merged data frame with common samples.
Load Proteomics or Metabolomics Data
load_omics(file, type = c("proteomics", "metabolomics"))load_omics(file, type = c("proteomics", "metabolomics"))
file |
Path to data file (.csv or .tsv) |
type |
Type of omics data ("proteomics" or "metabolomics") |
A data frame containing the omics dataset
## Not run: data <- load_omics("data.csv", type = "proteomics") ## End(Not run)## Not run: data <- load_omics("data.csv", type = "proteomics") ## End(Not run)
Normalize Omics Data
normalize_omics(data, method = c("zscore", "log2"))normalize_omics(data, method = c("zscore", "log2"))
data |
A numeric data frame of omics values. |
method |
Normalization method ("zscore", "log2", "quantile"). |
Normalized data frame.