Technical helpsheet

Technical requirements for data analysis

Some of the tools on this course utilise online, browser-based resources. You will find it useful to have a locally installed version of free molecular visualisation programs, we provide links below. Please note the links take you to external webpages not managed by EMBL.

The following tools were used for executing the practicals in this course:

SoftwareURLObservations
Rhttps://cran.r-project.org/bin/linux/ubuntu/Latest release – at least 4.2.1
FastQChttp://www.bioinformatics.babraham.ac.uk/projects/fastqc/fastqc_latest.zipLatest release
Hisathttps://cloud.biohpc.swmed.edu/index.php/s/oTtGWbWjaxsQ2Ho/downloadV 2 2.2.1
MultiQCLatest release
Cutadapthttps://cutadapt.readthedocs.io/en/stable/installation.htmlLatest release (use pip package manager for Python packages for installing not conda)
Trim_galorehttps://github.com/FelixKrueger/TrimGalore/archive/refs/tags/0.6.7.tar.gzLatest release
Samtoolshttps://github.com/samtools/samtools/releases/download/1.16.1/samtools-1.16.1.tar.bz2Latest release
SeqMonkhttps://www.bioinformatics.babraham.ac.uk/projects/seqmonk/seqmonk_v1.48.1_linux64.tar.gzLatest release
R packagesDESeq2 edgeR Rtsne limma statmod fastseg (will be installed by SeqMonk when first launched)
Reference-based mapping datahttps://www.bioinformatics.babraham.ac.uk/training/RNASeq_Course/yeast_data.tar.gz
Reference-based analysis datahttps://www.bioinformatics.babraham.ac.uk/training/RNASeq_Course/mouse_mapped_data.zip
Trinityhttps://github.com/trinityrnaseq/trinityrnaseq
De novo analysis datahttps://github.com/trinityrnaseq/RNASeq_Trinity_Tuxedo_Workshop/tree/master/RNASEQ_data
STARhttps://github.com/alexdobin/STAR
Scallophttps://github.com/Kingsford-Group/scallop/releases/tag/v0.10.5Latest release
Integrative genomics viewerhttps://software.broadinstitute.org/software/igv/Latest release

During the live virtual course, most of these tools were installed on Virtual Machines with the Linux-based Operating System Ubuntu 20.04.