*gsa.out: truncated `VARIABLE` names

1. Bug description

For some reason, MAGMA decided to truncate the VARIABLE column in their gsa.out files. This screws up attempts to match up the celltype names with those in the CTD.

Not sure if this was always the case, or I'm just noticing now because I'm using some CTDs with long celltype names (e.g. HumanCellLandscape)

Console output

Screenshot 2023-04-13 at 12 53 53

Expected behaviour

MAGMA.Celltyping can read in the results files without hitting an error.

2. Reproducible example

Code

magma_dirs <- MAGMA.Celltyping::import_magma_files(ids = c("ieu-a-298"))

ctd <- MAGMA::get_ctd("ctd_HumanCellLandscape")
 res <- MAGMA.Celltyping::celltype_associations_pipeline(
    ctd = ctd, 
    ctd_name ="ctd_HumanCellLandscape", 
    ctd_species = "human",
    magma_dirs = magma_dirs,  
    run_linear = TRUE, 
    run_top10 = TRUE, 
    upstream_kb = 35, 
    downstream_kb = 10, 
    force_new = TRUE,
    save_dir=here::here("processed_data/MAGMA"))

3. Session info

``` R Under development (unstable) (2023-03-02 r83926) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 22.04.2 LTS Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0 locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 [6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C time zone: Etc/UTC tzcode source: system (glibc) attached base packages: [1] stats graphics grDevices utils datasets methods base loaded via a namespace (and not attached): [1] fs_1.6.1 matrixStats_0.63.0 bitops_1.0-7 lubridate_1.9.2 devtools_2.4.5 [6] webshot_0.5.4 RColorBrewer_1.1-3 httr_1.4.5 doParallel_1.0.17 dynamicTreeCut_1.63-1 [11] gh_1.4.0 numDeriv_2016.8-1.1 profvis_0.3.7 tools_4.3.0 MAGMA.Celltyping_2.0.9 [16] backports_1.4.1 utf8_1.2.3 R6_2.5.1 uwot_0.1.14 lazyeval_0.2.2 [21] withr_2.5.0 urlchecker_1.0.1 gridExtra_2.3 prettyunits_1.1.1 preprocessCore_1.61.0 [26] WGCNA_1.72-1 cli_3.6.1 Biobase_2.59.0 TSP_1.2-4 askpass_1.1 [31] ewceData_1.7.1 Rsamtools_2.15.3 yulab.utils_0.0.6 foreign_0.8-84 R.utils_2.12.2 [36] sessioninfo_1.2.2 plotrix_3.8-2 BSgenome_1.67.4 orthogene_1.5.3 maps_3.4.1 [41] limma_3.55.7 readxl_1.4.2 impute_1.73.0 rstudioapi_0.14 RSQLite_2.3.1 [46] optimParallel_1.0-2 generics_0.1.3 gridGraphics_0.5-1 BiocIO_1.9.2 combinat_0.0-8 [51] dendextend_1.17.1 car_3.1-2 dplyr_1.1.1 homologene_1.4.68.19.3.27 GO.db_3.17.0 [56] Matrix_1.5-3 fansi_1.0.4 S4Vectors_0.37.5 abind_1.4-5 R.methodsS3_1.8.2 [61] lifecycle_1.0.3 scatterplot3d_0.3-43 yaml_2.3.7 carData_3.0-5 SummarizedExperiment_1.29.1 [66] clusterGeneration_1.3.7 BiocFileCache_2.7.2 grid_4.3.0 blob_1.2.4 promises_1.2.0.1 [71] ExperimentHub_2.7.1 crayon_1.5.2 miniUI_0.1.1.1 lattice_0.20-45 GenomicFeatures_1.51.4 [76] KEGGREST_1.39.0 MungeSumstats_1.7.19 pillar_1.9.0 knitr_1.42 GenomicRanges_1.51.4 [81] rjson_0.2.21 boot_1.3-28.1 codetools_0.2-19 fastmatch_1.1-3 glue_1.6.2 [86] ggfun_0.0.9 data.table_1.14.8 remotes_2.4.2 vctrs_0.6.1 png_0.1-8 [91] treeio_1.23.1 cellranger_1.1.0 gtable_0.3.3 assertthat_0.2.1 cachem_1.0.7 [96] xfun_0.38 mime_0.12 coda_0.19-4 survival_3.5-3 gargle_1.3.0 [101] seriation_1.4.2 SingleCellExperiment_1.21.1 RNOmni_1.0.1 iterators_1.0.14 interactiveDisplayBase_1.37.0 [106] ellipsis_0.3.2 nlme_3.1-162 ggtree_3.7.2 EWCE_1.7.4 usethis_2.1.6 [111] bit64_4.0.5 progress_1.2.2 filelock_1.0.2 googleAuthR_2.0.1 GenomeInfoDb_1.35.16 [116] rprojroot_2.0.3 rpart_4.1.19 Hmisc_5.0-1 colorspace_2.1-0 BiocGenerics_0.45.3 [121] DBI_1.1.3 nnet_7.3-18 phangorn_2.11.1 mnormt_2.1.1 tidyselect_1.2.0 [126] processx_3.8.0 bit_4.0.5 compiler_4.3.0 curl_5.0.0 httr2_0.2.2 [131] htmlTable_2.4.1 expm_0.999-7 xml2_1.3.3 ggdendro_0.1.23 DelayedArray_0.25.0 [136] plotly_4.10.1 rtracklayer_1.59.1 checkmate_2.1.0 scales_1.2.1 quadprog_1.5-8 [141] callr_3.7.3 rappdirs_0.3.3 stringr_1.5.0 digest_0.6.31 piggyback_0.1.4 [146] minqa_1.2.5 rmarkdown_2.21 ca_0.71.1 XVector_0.39.0 base64enc_0.1-3 [151] htmltools_0.5.5 pkgconfig_2.0.3 lme4_1.1-32 MatrixGenerics_1.11.1 dbplyr_2.3.2 [156] fastmap_1.1.1 rlang_1.1.0 htmlwidgets_1.6.2 shiny_1.7.4 jsonlite_1.8.4 [161] BiocParallel_1.33.12 R.oo_1.25.0 VariantAnnotation_1.45.1 RCurl_1.98-1.12 magrittr_2.0.3 [166] Formula_1.2-5 GenomeInfoDbData_1.2.10 ggplotify_0.1.0 patchwork_1.1.2 munsell_0.5.0 [171] Rcpp_1.0.10 viridis_0.6.2 ape_5.7-1 babelgene_22.9 stringi_1.7.12 [176] zlibbioc_1.45.0 MASS_7.3-58.3 AnnotationHub_3.7.4 plyr_1.8.8 pkgbuild_1.4.0 [181] parallel_4.3.0 Biostrings_2.67.2 splines_4.3.0 hms_1.1.3 ps_1.7.4 [186] fastcluster_1.2.3 igraph_1.4.2 ggpubr_0.6.0 ggsignif_0.6.4 reshape2_1.4.4 [191] biomaRt_2.55.4 stats4_4.3.0 pkgload_1.3.2 gprofiler2_0.2.1 BiocVersion_3.17.1 [196] XML_3.99-0.14 evaluate_0.20 BiocManager_1.30.20 nloptr_2.0.3 foreach_1.5.2 [201] httpuv_1.6.9 openssl_2.0.6 grr_0.9.5 tidyr_1.3.0 purrr_1.0.1 [206] heatmaply_1.4.2 ggplot2_3.4.2 broom_1.0.4 xtable_1.8-4 restfulr_0.0.15 [211] gitcreds_0.1.2 phytools_1.5-1 tidytree_0.4.2 rstatix_0.7.2 later_1.3.0 [216] viridisLite_0.4.1 googledrive_2.1.0 tibble_3.2.1 aplot_0.1.10 registry_0.5-1 [221] memoise_2.0.1 AnnotationDbi_1.61.2 GenomicAlignments_1.35.1 IRanges_2.33.1 cluster_2.1.4 [226] HGNChelper_0.8.1 timechange_0.2.0 here_1.0.1 ```

neurogenomics / MAGMA_Celltyping