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DEx Multi-Omics in Parkinson Disease (PD)

Description

In this repository is presented demo files and R scripts to reproduce one of the bioinformatic pipelines (framework A) and some of the visualization available in the manuscript Multi-omic landscaping of human midbrains identifies disease-relevant molecular targets and pathways in advanced-stage Parkinson's disease, published in Clinical Translational Medicine (2022).

Particularly, here you can find functions to ellaborate differential expression analyses of RNA-seq data (total and small RNA) using the Bioconductor packages DESeq2 and TCGAbiolinks.

Usage

Demo files are provided to conduct the differential expression analysis. This can be found in the Data/ folder. Nevertheless, please check the manuscript to access the multi-omics data used for the study.

This project was conducted in R software. As mention previously, here we present one of the bioinformatic pipelines available in our manuscript (framework A), in the R Scripts/ folder. However, for the other bioinformatic methodology (framework B), please revert to this GitHub page.

Bear in mind, here is only provided an adaptation of the original source code.

All the necessary R package dependencies are

  • ggplot2
  • magrittr
  • ggpubr
  • readxl
  • readr
  • dplyr
  • nortest
  • tidyverse
  • plyr
  • ashr
  • plm

These packages and dependencies should be installed a priori using the install.packages() function and complemented by the library() function to be ready to use.

Furthermore, we also leveraged packages available in the Bioconductor:

  • edgeR
  • limma
  • biomaRt
  • DESeq2
  • apeglm
  • vsn
  • TCGAbiolinks

Similarly, to employ these packages, first install the BiocManager package using install.packages("BiocManager"), and later the packages above using BiocManager::install().

For the RNA decomposition, we used the immunedeconv R package. This can be installed using the query:

install.packages("remotes")
remotes::install_github("icbi-lab/immunedeconv")

Contact

For any inquiries related to this work, please contact me via e-mail ana.galhoz@helmholtz-muenchen.de

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Bioinformatic differential expression analyses pipeline to investigate biomarkers in Parkinson disease.

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