SEMbap/README.md

In fernandoPalluzzi/SEMgraph: Network Analysis and Causal Inference Through Structural Equation Modeling

SEMbap: Bow-free covariance search and data de-correlation

Mario Grassi and Barbara Tarantino

Correspondence to: [e-mail]

R session

R version 4.1.0 (2021-05-18) Platform: x86_64-apple-darwin17.0 (64-bit) Running under: macOS Big Sur 10.16

Matrix products: default LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib

locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages: [1] grid parallel stats4 stats graphics grDevices utils datasets methods base

other attached packages: [1] matrixcalc_1.0-6 logger_0.2.2 org.Hs.eg.db_3.13.0 AnnotationDbi_1.54.1 [5] IRanges_2.26.0 S4Vectors_0.30.2 Biobase_2.52.0 BiocGenerics_0.38.0 [9] wesanderson_0.3.6 SEMdata_0.1.2 SEMgraph_1.1.4 lavaan_0.6-12 [13] igraph_1.3.5 ggplot2_1.0.1 data.table_1.14.4 dplyr_1.0.10 [17] mvtnorm_1.1-3 lrpsadmm_0.2.0

loaded via a namespace (and not attached): [1] httr_1.4.4 bit64_4.0.5 splines_4.1.0 assertthat_0.2.1 [5] blob_1.2.3 GenomeInfoDbData_1.2.6 yaml_2.3.6 robustbase_0.95-0 [9] pbivnorm_0.6.0 pillar_1.8.1 RSQLite_2.2.18 lattice_0.20-45 [13] glue_1.6.2 RcppEigen_0.3.3.9.2 digest_0.6.30 XVector_0.32.0 [17] RColorBrewer_1.1-3 colorspace_2.0-3 Matrix_1.5-1 plyr_1.8.7 [21] pcaPP_2.0-2 pkgconfig_2.0.3 zlibbioc_1.38.0 scales_1.2.1 [25] glasso_1.11 RSpectra_0.16-1 huge_1.3.5 tibble_3.1.8 [29] KEGGREST_1.32.0 mgcv_1.8-41 generics_0.1.3 cachem_1.0.6 [33] cli_3.4.1 mnormt_2.1.1 proto_1.0.0 magrittr_2.0.3 [37] crayon_1.5.2 memoise_2.0.1 fansi_1.0.3 nlme_3.1-160 [41] MASS_7.3-58.1 tools_4.1.0 lifecycle_1.0.3 stringr_1.4.1 [45] munsell_0.5.0 Biostrings_2.60.2 compiler_4.1.0 GenomeInfoDb_1.28.4 [49] rlang_1.0.6 RCurl_1.98-1.9 rstudioapi_0.14 cvTools_0.3.2 [53] bitops_1.0-7 boot_1.3-28 gtable_0.3.1 DBI_1.1.3 [57] reshape2_1.4.4 R6_2.5.1 fastmap_1.1.0 bit_4.0.4 [61] utf8_1.2.2 stringi_1.7.8 Rcpp_1.0.9 vctrs_0.5.0 [65] png_0.1-7 DEoptimR_1.0-11 tidyselect_1.2.0

SEMbap_code_data folder structure

This folder contains the following data and files that can be used to reproduce the analysis of the manuscript. The folder structure can be summarised as follows:

main_sim.R An R script to run Data simulations

main_real.R An R script to run breast cancer data analysis

help.R An R script with functions to import for running the analysis

trrust_rawdata.human.txt Transcription factor data

brca.RData Raw BRCA data

./csv/: simulations’ results

results_dense_100.csv results_dense_400.csv results_sparse_100.csv results_sparse_400.csv

Installation note:

1. Set folder SEMbap_code_data as the current working directory.
2. Specify a smaller number of iterations by argument “seed_vec” to reduce computing time for data simulations.

fernandoPalluzzi/SEMgraph documentation built on Feb. 20, 2025, 4:27 p.m.