Unix shell scripts were used on the Lisa Compute Cluster of SURFsara using modules "2019" and "Anaconda3". In most cases Python3 was used with dependencies bitarray (0.8.3), nose (1.3.7), numpy (1.18.1), pandas (0.24.2), pybedtools (0.8.0), and scipy (1.2.1). However, the LDSC software had some compatibility issues for Python3, hence incidental switches were made to Python2 with different versions for numpy (1.15.4) and pandas (0.18.1).
LDSC software was orignally written in Python2 by Bulik-Sulivan et al. (2015) and can be found here: https://github.com/bulik/ldsc. A Python3-compatible version can be found here: https://github.com/shz9/ldsc.
The original shell script for the rg-matrix can be found here: https://github.com/hillfung/rg-matrix.
Annotation files were constructed in R using functions available here: https://github.com/hillfung/make_LDSR_annot.
LDSC network plots were adapted from R code of Kanai et al. (2018), which can be found here: https://github.com/mkanai/ldsc-network-plot.
A wide array of R packages has been used for plotting figures (e.g. Script Functions.R, ldsc network plots.R), calculating the number of significant GWAS loci per disorder (Script Data Table1.R), and performing analyses of tissue-, developmental period- and cell type-specific enrichment (script results CTS_analyses.R), differential expression of developmental periods (Script differential expression analysis.R), and making annotation files for these developmental periods (Script differential expression analysis.R). For this, we made use of R (Version 3.6.2; R Core Team, 2019) and the R-packages Biobase (Version 2.46.0; W. Huber et al., 2015), BiocGenerics (Version 0.32.0; Huber et al., 2015), BiocParallel (Version 1.20.1; M. Morgan et al., 2019b), corrplot2017 (Wei & Simko, 2017), cowplot (Version 1.0.0; Wilke, 2019), data.table (Version 1.12.8; Dowle & Srinivasan, 2019), DelayedArray (Version 0.12.2; Pagès, Peter Hickey, & Lun, 2020), DESeq2 (Version 1.26.0; Love et al., 2014), dplyr (Version 0.8.4; Wickham et al., 2020), forcats (Version 0.4.0; Wickham, 2019a), Formula (Version 1.2.3; Zeileis & Croissant, 2010), GenomeInfoDb (Version 1.22.0; Arora, Morgan, Carlson, & Pagès, 2019), GenomicRanges (Version 1.38.0; M. Lawrence et al., 2013a), ggplot2 (Version 3.2.1; Wickham, 2016), Hmisc (Version 4.3.0; Harrell Jr, Charles Dupont, & others., 2019), igraph (Version 1.2.4.2; Csardi & Nepusz, 2006), IRanges (Version 2.20.1; M. Lawrence et al., 2013b), kableExtra (Version 1.1.0; Zhu, 2019), lattice (Version 0.20.38; Sarkar, 2008), matrixStats (Version 0.55.0; Bengtsson, 2019), papaja (Version 0.1.0.9942; Aust & Barth, 2020), purrr (Version 0.3.3; Henry & Wickham, 2019), qgraph (Version 1.6.4; Epskamp, Cramer, Waldorp, Schmittmann, & Borsboom, 2012), qvalue (Version 2.18.0; Storey, Bass, Dabney, & Robinson, 2019), RColorBrewer (Version 1.1.2; Neuwirth, 2014), readr (Version 1.3.1; Wickham, Hester, & Francois, 2018), S4Vectors (Version 0.24.1; Pagès, Lawrence, & Aboyoun, 2019), stringr (Version 1.4.0; Wickham, 2019b), SummarizedExperiment (Version 1.16.1; M. Morgan et al., 2019a), survival (Version 3.1.8; Terry M. Therneau & Patricia M. Grambsch, 2000), tibble (Version 2.1.3; Müller & Wickham, 2019), tidyr (Version 1.0.2; Wickham & Henry, 2020), and tidyverse (Version 1.3.0; Wickham, Averick, et al., 2019).
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