Technical help sheet
Introductory computational and data visualisation skills
| Rstudio & R | https://posit.co/products/open-source/rstudio/ |
| R libraries: tidyverse, ggplot2, gProfiler2 | install.packages(c(“tidyverse”, “gprofiler2”) |
Genome variation across human populations
| Variant Effect Predictor (either the command line script or its docker image) | https://www.ensembl.org/info/docs/tools/vep/index.html |
| Samtools v1.12 | http://www.htslib.org/download/ |
| Bcftools v1.12 | http://www.htslib.org/download/ |
| GATK v4.2.0.0 | https://github.com/broadinstitute/gatk/releases |
| BWA | https://sourceforge.net/projects/bio-bwa/files/bwa-0.7.17.tar.bz2/download |
| IGV (The web browser version should be fine) | https://igv.org/ |
| VEP | https://www.ensembl.org/info/docs/tools/vep/script/vep_tutorial.html |
| Data for VEP | https://ftp.ensembl.org/pub/current_variation/indexed_vep_cache/ homo_sapiens_vep_109_GRCh38.tar.gz |
Modelling cell signalling pathways
| COPASI | http://copasi.org/ |
| Jupytor Notebook with Tellurium Package installed | https://tellurium.readthedocs.io/en/latest/installation.html |
Interpreting functional information from large scale protein structure data
| PyMol | https://pymol.org/2/ |
| Jupyter | https://jupyter.org/ |
| CCP4 | https://www.ccp4.ac.uk/download/download_file.php?pkg=setup-64&os=linux&sid=ae2fafe0f387f669960cfa4fc9e7e85b0d570c7f |
| Python with packages: sys, pprint, solrq, pandas, numpy, requests, matplotlib, ipython | https://www.python.org/ |
| VSCode | https://code.visualstudio.com/sha/download?build=stable&os=linux-deb-x64 |
Networks and pathways
| Cytoscape | https://cytoscape.org/ |
| Rstudio | https://www.rstudio.com/ |
| SummarizedExperiment R package | https://bioconductor.org/packages/release/bioc/html/SummarizedExperiment.html |
| limma R package | https://bioconductor.org/packages/release/bioc/html/limma.html |
| gprofiler2 | https://cran.r-project.org/web/packages/gprofiler2/index.html |
| tidyverse | https://www.tidyverse.org/ |