Given the increased need for autonomous work, the students are free to use any computers they prefer to for this work, including the computers provided by the university, the cloud Renku WSBIM2122 environment (see here for details) or their own computers. They should also make sure they have all the documents they need and use a system they are comfortable with during the presentations and final oral exam.
The group projects constitute a significant part of the work and final grades. The reports will be written in Rmarkdown (see 1 and references therein) and compiled into a final pdf file. It should be structure as a scientific manuscript or thesis, including:
An abstract, summarising the report.
A short introduction, providing the necessary background to understand the report.
A material and methods section describing the experimental design and the methods utilised.
A results section describing and interpreting the results.
A conclusion documenting the wider implications of the findings, possible follow-up experiments or analyses and any limitations of the methods and results discussed above.
An author contributions section documenting the respective contributions of all authors. This section is particularly important as it will help us assess you involvement in the projects and guide the discussions during the oral exam. While all authors are expected to have contributed to the work and report, some will probably have specifically focused on different aspects of the work. These are areas where will dwell into more details.
Before handing in your reports, each group will present their preliminary results. The group is free to choose the type of support they want to use (slides, a report, an Rmd file, … ). The emphasis of the presentations will not be to present a polished report, but for students and instructors to ask questions to highlight possible improvements. You will then be able to use the output of these questions and discussions, including those with other groups, to improve your own group report.
The following packages have been used to generate this document.
## R version 4.4.0 (2024-04-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Manjaro Linux
##
## Matrix products: default
## BLAS: /usr/lib/libblas.so.3.12.0
## LAPACK: /usr/lib/liblapack.so.3.12.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## time zone: Europe/Brussels
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] plotly_4.10.4 factoextra_1.0.7
## [3] gplots_3.1.3.1 limma_3.60.0
## [5] QFeatures_1.15.1 MultiAssayExperiment_1.30.1
## [7] PSMatch_1.8.0 magrittr_2.0.3
## [9] Spectra_1.14.0 ProtGenerics_1.36.0
## [11] BiocParallel_1.38.0 msigdbr_7.5.1
## [13] clusterProfiler_4.12.0 GO.db_3.19.1
## [15] org.Hs.eg.db_3.19.1 AnnotationDbi_1.66.0
## [17] patchwork_1.2.0 DESeq2_1.44.0
## [19] SummarizedExperiment_1.34.0 Biobase_2.64.0
## [21] MatrixGenerics_1.16.0 matrixStats_1.3.0
## [23] GenomicRanges_1.56.0 GenomeInfoDb_1.40.0
## [25] IRanges_2.38.0 S4Vectors_0.42.0
## [27] BiocGenerics_0.50.0 DT_0.33
## [29] lubridate_1.9.3 forcats_1.0.0
## [31] stringr_1.5.1 dplyr_1.1.4
## [33] purrr_1.0.2 readr_2.1.5
## [35] tidyr_1.3.1 tibble_3.2.1
## [37] tidyverse_2.0.0 ggplot2_3.5.1
## [39] rWSBIM2122_0.4.1
##
## loaded via a namespace (and not attached):
## [1] splines_4.4.0 later_1.3.2
## [3] bitops_1.0-7 ggplotify_0.1.2
## [5] polyclip_1.10-6 preprocessCore_1.66.0
## [7] lifecycle_1.0.4 rstatix_0.7.2
## [9] lattice_0.22-6 vroom_1.6.5
## [11] MASS_7.3-60.2 crosstalk_1.2.1
## [13] backports_1.4.1 sass_0.4.9
## [15] rmarkdown_2.26 jquerylib_0.1.4
## [17] yaml_2.3.8 httpuv_1.6.15
## [19] MsCoreUtils_1.16.0 cowplot_1.1.3
## [21] DBI_1.2.2 RColorBrewer_1.1-3
## [23] abind_1.4-5 zlibbioc_1.50.0
## [25] AnnotationFilter_1.28.0 ggraph_2.2.1
## [27] yulab.utils_0.1.4 tweenr_2.0.3
## [29] GenomeInfoDbData_1.2.12 enrichplot_1.24.0
## [31] ggrepel_0.9.5 tidytree_0.4.6
## [33] BiocStyle_2.32.0 ncdf4_1.22
## [35] codetools_0.2-20 DelayedArray_0.30.0
## [37] DOSE_3.30.0 xml2_1.3.6
## [39] ggforce_0.4.2 tidyselect_1.2.1
## [41] aplot_0.2.2 UCSC.utils_1.0.0
## [43] farver_2.1.1 viridis_0.6.5
## [45] jsonlite_1.8.8 tidygraph_1.3.1
## [47] bbmle_1.0.25.1 tools_4.4.0
## [49] ExploreModelMatrix_1.16.0 msdata_0.44.0
## [51] treeio_1.28.0 Rcpp_1.0.12
## [53] glue_1.7.0 BiocBaseUtils_1.6.0
## [55] gridExtra_2.3 SparseArray_1.4.1
## [57] xfun_0.43 qvalue_2.36.0
## [59] shinydashboard_0.7.2 withr_3.0.0
## [61] numDeriv_2016.8-1.1 BiocManager_1.30.23
## [63] fastmap_1.1.1 fansi_1.0.6
## [65] shinyjs_2.1.0 caTools_1.18.2
## [67] digest_0.6.35 timechange_0.3.0
## [69] R6_2.5.1 mime_0.12
## [71] gridGraphics_0.5-1 colorspace_2.1-0
## [73] gtools_3.9.5 RSQLite_2.3.6
## [75] utf8_1.2.4 generics_0.1.3
## [77] data.table_1.15.4 graphlayouts_1.1.1
## [79] httr_1.4.7 htmlwidgets_1.6.4
## [81] S4Arrays_1.4.0 scatterpie_0.2.2
## [83] pkgconfig_2.0.3 gtable_0.3.5
## [85] blob_1.2.4 XVector_0.44.0
## [87] shadowtext_0.1.3 htmltools_0.5.8.1
## [89] carData_3.0-5 bookdown_0.34.2
## [91] fgsea_1.30.0 clue_0.3-65
## [93] rintrojs_0.3.4 scales_1.3.0
## [95] png_0.1-8 ggfun_0.1.4
## [97] MetaboCoreUtils_1.12.0 knitr_1.46
## [99] rstudioapi_0.16.0 tzdb_0.4.0
## [ reached getOption("max.print") -- omitted 54 entries ]To install all necessary packages to run all the code, please execute the following code:
pkgs <- c("AnnotationDbi", "base", "Biobase", "BiocGenerics",
"BiocParallel", "clusterProfiler", "datasets", "DESeq2", "dplyr", "DT",
"factoextra", "forcats", "GenomeInfoDb", "GenomicRanges", "ggplot2",
"GO.db", "gplots", "graphics", "grDevices", "IRanges", "limma",
"lubridate", "magrittr", "MatrixGenerics", "matrixStats", "methods",
"msigdbr", "MultiAssayExperiment", "org.Hs.eg.db", "patchwork",
"plotly", "ProtGenerics", "PSMatch", "purrr", "QFeatures", "readr",
"rWSBIM2122", "S4Vectors", "Spectra", "stats", "stats4", "stringr",
"SummarizedExperiment", "tibble", "tidyr", "tidyverse", "utils")Page built: 2024-05-25 using R version 4.4.0 (2024-04-24)