INTERACTIVE COMPETENCY MODEL
Build Your Analyst Skill Stack
Open each layer to see what to learn, why it matters, useful tools and the practical checkpoint that shows progress.
01FOUNDATIONBiological Foundations+
Learn: DNA, RNA, proteins, genes, genomes, gene expression and variation.
Why analysts need it: Data has meaning only when connected to a biological question.
- Molecular biology
- Genetics
- Genomics
02COMPUTELinux & Bash+
Learn: navigation, file operations, pipes, redirection and basic Bash.
Why analysts need it: Most large-scale bioinformatics workflows run in Linux environments.
- Linux
- Bash
- grep
- awk
- sed
03PROGRAMPython+
Learn: variables, collections, functions, loops, file parsing and data frames.
Why analysts need it: Python automates repetitive work and supports flexible data processing.
- Python
- pandas
- Biopython concepts
04ANALYZER+
Learn: vectors, data frames, tidy data, statistical testing and plotting.
Why analysts need it: R is central to statistical bioinformatics and transcriptomics.
- R
- Bioconductor
- ggplot2
05MEASUREStatistics+
Learn: distributions, variance, hypothesis testing, p-values, multiple testing, correlation and fold change.
Why analysts need it: Statistical reasoning separates patterns from unsupported conclusions.
- Descriptive statistics
- Inference
- Experimental design
06RETRIEVEBiological Databases+
Learn: accession numbers, metadata, records, database scope and responsible retrieval.
Why analysts need it: Public databases provide reference sequences and research datasets.
- NCBI
- Ensembl
- GEO
- SRA
- UniProt
07COMPARESequence Analysis+
Learn: similarity, homology, pairwise and multiple alignment, reference sequences and annotation.
Why analysts need it: Sequence comparison supports identification and functional inference.
- BLAST
- Alignment concepts
- FASTA
08PROCESSNGS+
Learn: reads, quality scores, QC, preprocessing, alignment, assembly and common NGS file formats.
Why analysts need it: Sequencing data drives modern genomics and molecular research.
- FASTQ
- FastQC
- SAM/BAM
- VCF
09QUANTIFYTranscriptomics+
Learn: RNA-Seq QC, alignment, quantification, normalization and differential expression.
Why analysts need it: Transcriptomics connects sequencing measurements to gene activity.
- RNA-Seq
- featureCounts concepts
- Differential expression
10DETECTVariant Analysis+
Learn: reference alignment, variant calling concepts, filtering, annotation and interpretation limits.
Why analysts need it: Variant analysis connects sequence differences with biological questions.
- WGS/WES concepts
- VCF
- Variant filtering
11COMMUNICATEVisualization+
Learn: chart selection, visual hierarchy, labels, color, uncertainty and publication-quality export.
Why analysts need it: Clear figures reveal patterns and communicate evidence responsibly.
- ggplot2
- matplotlib
- Heatmaps
- PCA plots
12REPRODUCEReproducibility+
Learn: organized folders, scripts, parameters, environment notes, version control and readable documentation.
Why analysts need it: Another person should be able to understand and repeat the analysis.
- Git
- GitHub
- README
- Workflow documentation
13DEMONSTRATEPortfolio Projects+
Learn: question framing, scope control, end-to-end analysis, interpretation and presentation.
Why analysts need it: Projects show integrated competency more clearly than tool lists.
- Public datasets
- Complete workflows
- Technical reporting
