Digital Competences

Next-generation sequencing

Genome (WGS, WES and targeted sequencing), epigenome (STARRseq, ChIPseq, ATACseq) and transcriptome
(RNAseq) next-generation sequencing data analysis.

FastQ QC (FastQC), trimming (Trim Galore), alignment (Bowtie2) and generation of SAM, BAM and BigWig files (samtools, bedtools).

Sequencing metrics (coverage, on-target, duplication rate, GC-bias) quantification to assess the efficiency and specificity of sequencing experiments (Picard Metrics).

Visual exploration of alignments and coverage enrichment using IGV, UCSC Genome Browser and seqmonk.

Peak calling (STARRpeaker, MACS2), differential expression analysis (DESeq2), variant calling (GATK).

Variant classification and interpretation.

Multi-omics data visualization with deeptools, ggplot2, IGV web app.

Programming and software

Unix and Conda for environment management.

Visual Studio Code and Jupyter Notebook for code development, editing, sharing and communication.

Cluster computing environments (Babraham Compute Cluster) and cluster workload managers (SLURM).

Git and GitHub for version control.

Scripting languages

Bash scripting

Python:

data processing/analysis: Pandas, Numpy
data visualization: Matplotlib, Seaborn
deeplearning model: Keras, TensorFlow

data processing/analysis: tidyverse
data visualization: ggplot2
statistics: core R, rstatix, power calculation

SQLite

Miscellaneous

Transcription factor enrichment: HOMER, meme-suite

Pathway enrichment analysis: Gene Ontology, GSEA

Bigdata biological databases: Ensembl, 1000Genomes, Human Protein Atlas, TCGA, COSMIC