gptomics/bioskills

1

bio-single-cell-perturb-seq Analyze Perturb-seq / CROP-seq single-cell CRISPR screens. Use when assigning guides as a mixture problem, removing n…

gptomics/bioskills

4

2

bio-single-cell-preprocessing Quality control, ambient-RNA handling, normalization, and feature selection for single-cell RNA-seq using Scanpy (Pyt…

gptomics/bioskills

4

3

bio-single-cell-scatac-analysis Analyze single-cell ATAC-seq with Signac/ArchR (R) and SnapATAC2 (Python alternative). Use when processing scATAC fra…

gptomics/bioskills

4

4

bio-single-cell-trajectory-inference Infers developmental trajectories, pseudotime, RNA velocity, and directed fate probabilities from single-cell data us…

gptomics/bioskills

4

5

bio-spatial-transcriptomics-image-analysis Segments cells/nuclei and extracts image features from imaging spatial transcriptomics (Xenium, MERFISH/MERSCOPE, Cos…

gptomics/bioskills

4

6

bio-spatial-transcriptomics-spatial-communication Maps cell-cell communication and ligand-receptor co-expression in spatial transcriptomics (Visium, Xenium, MERFISH, C…

gptomics/bioskills

4

7

bio-spatial-transcriptomics-spatial-neighbors Build the spatial neighbor graph that every downstream spatial statistic (Moran's I, neighborhood enrichment, co-occu…

gptomics/bioskills

4

8

bio-workflow-management-cwl-workflows Create portable, standards-based bioinformatics pipelines with Common Workflow Language (CWL). Use when building work…

gptomics/bioskills

4

9

bio-workflow-management-snakemake-workflows Build reproducible bioinformatics pipelines with Snakemake using rules, wildcards, and automatic dependency resolutio…

gptomics/bioskills

4

10

bio-workflows-expression-to-pathways Workflow from differential expression results to functional enrichment analysis. Covers GO, KEGG, Reactome enrichment…

gptomics/bioskills

4

11

bio-workflows-genome-assembly-pipeline End-to-end genome assembly workflow from reads to polished assembly with QC. Supports short reads (SPAdes), long read…

gptomics/bioskills

4

12

bio-workflows-metagenomics-pipeline End-to-end metagenomics workflow from FASTQ to taxonomic and functional profiles. Covers Kraken2 classification, Brac…

gptomics/bioskills

4

13

bio-alignment-filtering Filter alignments by flags, mapping quality, and regions using samtools view and pysam. Use when extracting specific …

gptomics/bioskills

3

14

bio-alignment-pairwise Perform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner. Use when comparing two sequences, find…

gptomics/bioskills

3

15

bio-atac-seq-atac-peak-calling Call accessible chromatin regions from ATAC-seq data using MACS3 with ATAC-specific parameters. Use when identifying …

gptomics/bioskills

3

16

bio-atac-seq-footprinting Detect transcription factor binding sites through footprinting analysis in ATAC-seq data using TOBIAS. Use when ident…

gptomics/bioskills

3

17

bio-batch-processing Process multiple sequence files in batch using Biopython. Use when working with many files, merging/splitting sequenc…

gptomics/bioskills

3

18

bio-bedgraph-handling Create, manipulate, and convert bedGraph files for genome browser visualization. Covers bedGraph format, conversion t…

gptomics/bioskills

3

19

bio-chip-seq-super-enhancers Identifies super-enhancers from H3K27ac ChIP-seq data using ROSE and related tools. Use when studying cell identity g…

gptomics/bioskills

3

20

bio-clinical-databases-dbsnp-queries Query dbSNP for rsID lookups, variant annotations, and cross-references to other databases. Use when mapping between …

gptomics/bioskills

3

21

bio-clinical-databases-variant-prioritization Filter and prioritize variants by pathogenicity, population frequency, and clinical evidence for rare disease analysi…

gptomics/bioskills

3

22

bio-clip-seq-clip-peak-calling Call protein-RNA binding site peaks from CLIP-seq data using CLIPper, PureCLIP, or Piranha. Use when identifying RBP …

gptomics/bioskills

3

23

bio-copy-number-gatk-cnv Call copy number variants using GATK best practices workflow. Supports both somatic (tumor-normal) and germline CNV d…

gptomics/bioskills

3

24

bio-data-visualization-interactive-visualization Create interactive HTML plots with plotly and bokeh for exploratory data analysis and web-based sharing of omics visu…

gptomics/bioskills

3

25

bio-de-edger-basics Perform differential expression analysis using edgeR in R/Bioconductor. Use for analyzing RNA-seq count data with the…

gptomics/bioskills

3

26

bio-de-results Extract, filter, annotate, and export differential expression results from DESeq2 or edgeR. Use for identifying signi…

gptomics/bioskills

3

27

bio-entrez-link Find cross-references between NCBI databases using Biopython Bio.Entrez. Use when navigating from genes to proteins, …

gptomics/bioskills

3

28

bio-epitranscriptomics-m6anet-analysis Detect m6A modifications from Oxford Nanopore direct RNA sequencing using m6Anet. Use when analyzing epitranscriptomi…

gptomics/bioskills

3

29

bio-format-conversion Convert between sequence file formats (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO. Use when changing file…

gptomics/bioskills

3

30

bio-gatk-variant-calling Variant calling with GATK HaplotypeCaller following best practices. Covers germline SNP/indel calling, GVCF workflow …

gptomics/bioskills

3

31

bio-genome-assembly-scaffolding Scaffold contigs into chromosome-level assemblies using Hi-C data with YaHS, 3D-DNA, SALSA2, and validate with BUSCO …

gptomics/bioskills

3

32

bio-genome-intervals-bigwig-tracks Create and read bigWig browser tracks for visualizing continuous genomic data. Convert bedGraph to bigWig, extract si…

gptomics/bioskills

3

33

bio-geo-data Query NCBI Gene Expression Omnibus (GEO) for expression datasets using Biopython Bio.Entrez. Use when finding microar…

gptomics/bioskills

3

34

bio-imaging-mass-cytometry-cell-segmentation Cell segmentation from multiplexed tissue images. Covers deep learning (Cellpose, Mesmer) and classical approaches fo…

gptomics/bioskills

3

35

bio-imaging-mass-cytometry-phenotyping Cell type assignment from marker expression in IMC data. Covers manual gating, clustering, and automated classificati…

gptomics/bioskills

3

36

bio-long-read-sequencing-clair3-variants Deep learning-based variant calling from long reads using Clair3 for SNPs and small indels. Use when calling germline…

gptomics/bioskills

3

37

bio-longread-qc Quality control for long-read sequencing data using NanoPlot, NanoStat, and chopper. Generate QC reports, filter read…

gptomics/bioskills

3

38

bio-metabolomics-statistical-analysis Statistical analysis for metabolomics data. Covers univariate testing, multivariate methods (PCA, PLS-DA), and biomar…

gptomics/bioskills

3

39

bio-metabolomics-xcms-preprocessing XCMS3 workflow for LC-MS/MS metabolomics preprocessing. Covers peak detection, retention time alignment, corresponden…

gptomics/bioskills

3

40

bio-methylation-calling Extract methylation calls from Bismark BAM files using bismark_methylation_extractor. Generates per-cytosine reports …

gptomics/bioskills

3

41

bio-methylation-dmr-detection Differentially methylated region (DMR) detection using methylKit tiles, bsseq BSmooth, and DMRcate. Use when identify…

gptomics/bioskills

3

42

bio-methylation-methylkit DNA methylation analysis with methylKit in R. Import Bismark coverage files, filter by coverage, normalize samples, a…

gptomics/bioskills

3

43

bio-paired-end-fastq Handle paired-end FASTQ files (R1/R2) using Biopython. Use when working with Illumina paired reads, synchronizing pai…

gptomics/bioskills

3

44

bio-pdb-geometric-analysis Perform geometric calculations on protein structures using Biopython Bio.PDB. Use when measuring distances, angles, a…

gptomics/bioskills

3

45

bio-pdb-structure-io Parse and write protein structure files using Biopython Bio.PDB. Use when reading PDB, mmCIF, and MMTF files, downloa…

gptomics/bioskills

3

46

bio-population-genetics-association-testing Genome-wide association studies (GWAS) with PLINK. Perform case-control and quantitative trait association testing us…

gptomics/bioskills

3

47

bio-population-genetics-linkage-disequilibrium Calculate linkage disequilibrium statistics (r², D'), perform LD pruning for population structure analysis, identify …

gptomics/bioskills

3

48

bio-population-genetics-plink-basics PLINK file formats, format conversion, and quality control filtering for population genetics. Convert between VCF, BE…

gptomics/bioskills

3

49

bio-population-genetics-population-structure Analyze population structure using PCA and admixture analysis with PLINK and ADMIXTURE. Identify population clusters,…

gptomics/bioskills

3

50

bio-population-genetics-scikit-allel-analysis Python population genetics with scikit-allel. Read VCF files, compute allele frequencies, calculate diversity statist…

gptomics/bioskills

3