Introduction
1.
Bioinformatics
1.1.
bioconda
1.2.
bioconductor
2.
Coding tools
2.1.
coding conventions
2.2.
integrated development environments (IDEs)
2.3.
licensing
2.4.
markdown syntax
2.5.
regular expressions
2.6.
user experience
2.7.
version control
3.
Command line
3.1.
Unix shell / linux command line
3.2.
conda (software installation)
3.3.
linux tools
4.
Data analyses
4.1.
differential expression analysis
4.2.
single cell analysis
5.
Data downloads / reanalysis
5.1.
SRA, ENA, NCBI, Ensembl
5.2.
TCGA, TARGET, GTEx
6.
Data formats and tools
6.1.
fastq: sequencing data
6.2.
tab-/comma-separated values
6.3.
YAML syntax
7.
Data presentation
7.1.
color palettes
7.2.
grammar of graphics
7.3.
interactive reporting
8.
Programming Languages
8.1.
python
8.2.
R
8.3.
Rust
9.
Reference data
9.1.
liftover between references
10.
Statistics
10.1.
bayesian statistics (priors, likelihoods and posterior distributions)
10.2.
frequentist statistics (hypothesis tests, p-values, etc.)
11.
Workflow management
11.1.
Nextflow
11.2.
Snakemake
12.
Working on servers
12.1.
persistent shell sessions (screen, tmux)
12.2.
ssh login
12.3.
data transfer
Light
Rust
Coal
Navy
Ayu
A collection of resources for data scientists (not only) in bioinformatics
Coding tools