Drug repurposing of bromodomain inhibitors as a novel therapeutic lead for lymphatic filariasis guided by multi-species transcriptomics

Matthew Chung

2019-09-17

The repository contains scripts and input_data_files to replicate the transcriptomics analysis in the manuscript. Additionally, the Supplementary Data for the manuscript is stored here.

System requirements

R scripts were run using Windows 10 x64 with RStudio v1.1.447 using this R session:

R version 3.5.0 (2018-04-23)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] ggdendro_0.1-20       pvclust_2.0-0         dendextend_1.9.0      factoextra_1.0.5      gridExtra_2.3         reshape_0.8.8        
 [7] ggplot2_3.1.0         gtools_3.8.1          WGCNA_1.66            fastcluster_1.1.25    dynamicTreeCut_1.63-1 edgeR_3.24.0         
[13] limma_3.38.2         

loaded via a namespace (and not attached):
 [1] matrixStats_0.54.0    robust_0.4-18         fit.models_0.5-14     bit64_0.9-7           doParallel_1.0.14     RColorBrewer_1.1-2   
 [7] rprojroot_1.3-2       prabclus_2.2-6        tools_3.5.0           backports_1.1.2       R6_2.3.0              rpart_4.1-13         
[13] Hmisc_4.1-1           DBI_1.0.0             lazyeval_0.2.1        BiocGenerics_0.28.0   colorspace_1.3-2      trimcluster_0.1-2.1  
[19] nnet_7.3-12           withr_2.1.2           tidyselect_0.2.5      bit_1.1-14            compiler_3.5.0        preprocessCore_1.44.0
[25] Biobase_2.42.0        htmlTable_1.12        labeling_0.3          diptest_0.75-7        scales_1.0.0          checkmate_1.8.5      
[31] DEoptimR_1.0-8        mvtnorm_1.0-8         robustbase_0.93-3     stringr_1.3.1         digest_0.6.18         foreign_0.8-70       
[37] rmarkdown_1.10        rrcov_1.4-4           base64enc_0.1-3       pkgconfig_2.0.2       htmltools_0.3.6       htmlwidgets_1.3      
[43] rlang_0.3.0.1         rstudioapi_0.8        RSQLite_2.1.1         impute_1.56.0         bindr_0.1.1           mclust_5.4.1         
[49] acepack_1.4.1         dplyr_0.7.6           magrittr_1.5          modeltools_0.2-22     GO.db_3.6.0           Formula_1.2-3        
[55] Matrix_1.2-14         Rcpp_1.0.0            munsell_0.5.0         S4Vectors_0.20.1      viridis_0.5.1         stringi_1.2.4        
[61] whisker_0.3-2         yaml_2.2.0            MASS_7.3-51.1         flexmix_2.3-14        plyr_1.8.4            blob_1.1.1           
[67] parallel_3.5.0        ggrepel_0.8.0         crayon_1.3.4          lattice_0.20-35       splines_3.5.0         locfit_1.5-9.1       
[73] knitr_1.20            pillar_1.3.0          fpc_2.1-11.1          codetools_0.2-15      stats4_3.5.0          glue_1.3.0           
[79] evaluate_0.12         latticeExtra_0.6-28   data.table_1.11.8     foreach_1.4.4         gtable_0.2.0          purrr_0.2.5          
[85] kernlab_0.9-27        assertthat_0.2.0      viridisLite_0.3.0     class_7.3-14          survival_2.41-3       pcaPP_1.9-73         
[91] tibble_1.4.2          iterators_1.0.10      AnnotationDbi_1.44.0  memoise_1.1.0         IRanges_2.16.0        bindrcpp_0.2.2

No non-standard hardware is required.

Installation

RStudio installation is required along with the packages listed as follows:

 [1] ggdendro_0.1-20       pvclust_2.0-0         dendextend_1.9.0      factoextra_1.0.5      gridExtra_2.3         reshape_0.8.8
 [7] ggplot2_3.1.0         gtools_3.8.1          WGCNA_1.66            fastcluster_1.1.25    dynamicTreeCut_1.63-1 edgeR_3.24.0         
[13] limma_3.38.2        

Typical install time for RStudio and the listed packages should be <15 min

Demo and Instructions for Use

Open Rmd scripts using RStudio and alter the input files to the files listed in the (3) input_data_files folder.

(1) scripts

The scripts folder contains three Rmd scripts used for the transcriptome analysis of each organism:

a) aaegypti_transcriptome_v2.Rmd

b) bmalayi_transcriptome_v2.Rmd

c) wbm_transcriptome_v2.Rmd

Each of the three scripts takes these inputs:

a) geneinfo - table containing functional annotation for the analyzed genes

b) counts - matrix of read counts for each gene, constructed as described in the Materials and Methods

c) tpm - matrix of TPM for each gene

d) groups - used to assign groups and colors for the different samples

e) output directory path

Change the "Input file paths" code block to run the scripts on your local system.

(2) htmls

Contains the output html files generated from the Rmd files in (1) scripts using the R package knitr. These are the expected outputs from each of the three scripts.

(3) input_data_files

For each of the Rmd files, the inputs are:

aaegypti_transcriptome.Rmd

geneinfo.path <- aaegypti_gene.info
counts.path <- aaegypti_counts.tsv
tpm.path <- aaegypti_tpm.tsv
groups.path <- aaegypti_groups.tsv

bmalayi_transcriptome.Rmd

geneinfo.path <- bmalayi_gene.info
counts.path <- bmalayi_counts.tsv
tpm.path <- bmalayi_tpm.tsv
groups.path <- bmalayi_groups.tsv

wbm_transcriptome.Rmd

geneinfo.path <- wbm_gene.info
counts.path <- wbm_counts.tsv
tpm.path <- wbm_tpm.tsv
groups.path <- wbm_groups.tsv

Each of these scripts should take <30 min.