Code for The Chagas Disease Antigen and Epitope Atlas

This is the web and electronic complement to the paper "A Trypanosoma cruzi Antigen and Epitope Atlas: deep characterization of individual antibody specificities in human Chagas Disease patients across the Americas."

The code demonstrates the processing and analysis of peptide microarray data as done for the Atlas. We make the code available so you can reproduce the results and play with the data. Do notice that all the outputs from running this pipeline are already available: Normalized Data is available at the EMBL-EBI Array Express database, and the Smoothed Data and Region Data are available as Supplementary Tables and Files in the paper.

Dependencies

The code is written in the R programming language, and depends on the following packages: data.table, preprocessCore and zoo for the antigenicity analysis, and dplyr and reshape2 for the alanine scan analysis (and optional pheatmap and colorblindr for ploting heatmaps).

Testing the code

By default this code will use the test datasets present in the test_data directory included in this repository.

Prefixes in the filenames and folder names in the repository are there simply to indicate grouping and order of execution.

The antigenicity analysis example for a subset of 20 proteins can be performed by running in UNIX into the main folder of this repository (the folder containing all the .R scripts):

$ Rscript 01_pools_normalize_data.R
$ Rscript 02_pools_smooth_data.R
$ Rscript 03_calculate_peaks.R
$ Rscript 04_calculate_regions.R
$ Rscript 11_individual_serums_normalize_data.R
$ Rscript 12_individual_serums_smooth_data.R

And the analysis of single-residue mutagenesis data (aka AlanineScan) in the test data for Ag2-antigen | TcCLB.511671.60 can be reproduced as in the example provided here by running in UNIX:

$ Rscript 21_alanine_scan_analisis.R

If you'd like to run the code from within Rstudio, you may want to set either the working directory (setwd function) or change the main_folder variable found in the CONFIG section in each of the script files to point towards the main folder of this repository.

Analyzing Peptide Microarray Data from the Atlas

To analyze the entire dataset you will need the following:

• The files included in this repository
• The raw data files from CHAGASTOPE-v1 arrays (such as AR_PO_raw.tsv) downloaded from Array Express here. Place them in chagastope_data/inputs/02_pools_raw_data.
• Raw data files from CHAGASTOPE-v2 arrays (such as AR_E1_PO_raw.tsv) downloaded from Array Express here. Place them in chagastope_data/inputs/12_individual_serums_raw_data.
• The mapping file for CHAGASTOPE-v1 arrays (Supplementary File S08 - Mapping of CHAGASTOPE-v1 data to T cruzi proteins.tsv), available in our paper. Place it in chagastope_data/inputs/01_pools_array_design.
• The mapping file for CHAGASTOPE-v2 arrays (Supplementary File S09 - Mapping of CHAGASTOPE-v2 data to T cruzi proteins.tsv), available in our paper. Place it in chagastope_data/inputs/11_individual_serums_array_design.

Download all data, place it in the proper location and run each script, adding -test F at the end, for example:

$ Rscript 01_pools_normalize_data.R -test F

Alternatively, edit each script and set:

#### CONFIG ####
testing <- FALSE

Also remember to change either the working directory or the main_folder variable if you are running this code directly from Rstudio.

Please Cite

A Trypanosoma cruzi Antigen and Epitope Atlas: deep characterization of antibody specificities in Chagas Disease patients across the Americas Alejandro D. Ricci, Leonel Bracco, Janine M. Ramsey, Melissa S. Nolan, M. Katie Lynn, Jaime Altcheh, Griselda Ballering, Faustino Torrico, Norival Kesper, Juan C. Villar, Jorge D. Marco, Fernán Agüero. bioRxiv 2022.08.19.504544; doi:10.1101/2022.08.19.504544

(This article is a preprint and has not been certified by peer review).