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.
Debugging
8.1.
debugging
9.
Programming Languages
9.1.
python
9.2.
R
9.3.
Rust
10.
Reference data
10.1.
liftover between references
11.
Statistics
11.1.
bayesian statistics (priors, likelihoods and posterior distributions)
11.2.
frequentist statistics (hypothesis tests, p-values, etc.)
12.
Workflow management
12.1.
Nextflow
12.2.
Snakemake
13.
Working on servers
13.1.
persistent shell sessions (screen, tmux)
13.2.
ssh login
13.3.
data transfer
Light
Rust
Coal
Navy
Ayu
A collection of resources for data scientists (not only) in bioinformatics
Workflow management