Discover blockchain bioinformatics skills, compare source repositories and read the instructions for each workflow.
Read and manipulate Flow Cytometry Standard (FCS) files. Covers loading data, accessing parameters, and basic data exploration. Use when loading and inspecting flow or mass cytometry data before preprocessing.
Gene Set Enrichment Analysis using clusterProfiler gseGO and gseKEGG. Uses a ranked gene list to find coordinated changes in gene sets without requiring arbitrary significance cutoffs. Detects subtle but coordi...
Transcribe DNA to RNA and translate to protein using Biopython. Use when converting between DNA, RNA, and protein sequences, finding ORFs, or using alternative codon tables.
Parse and analyze multiple sequence alignments using Biopython. Extract sequences, identify conserved regions, analyze gaps, work with annotations, and manipulate alignment data for downstream analysis.
Calculate linkage disequilibrium statistics (r², D'), perform LD pruning for population structure analysis, identify haplotype blocks, and visualize LD patterns using PLINK, scikit-allel, and LDBlockShow.
Load and parse mass spectrometry data formats including mzML, mzXML, and quantification tool outputs like MaxQuant proteinGroups.txt. Handles common preprocessing steps like contaminant filtering and missing va...
WikiPathways enrichment using clusterProfiler and rWikiPathways. Performs over-representation analysis and GSEA on community-curated biological pathways. WikiPathways is an open, collaborative platform with pat...
Compute spatial statistics for spatial transcriptomics data using Squidpy. Calculate Moran's I, Geary's C, spatial autocorrelation, co-occurrence analysis, and neighborhood enrichment.
Quantify transcript expression using pseudo-alignment with Salmon or kallisto. Use for fast, accurate transcript-level quantification directly from FASTQ files without genome alignment.
Map metabolites to biological pathways using KEGG, Reactome, and MetaboAnalyst. Perform pathway enrichment and topology analysis. Use when interpreting metabolomics results in the context of biochemical pathway...
Align DNA short reads to reference genomes using bwa-mem2, the faster successor to BWA-MEM. Use for whole genome sequencing, exome sequencing, and ChIP-seq alignment.
Detect antimicrobial resistance genes using AMRFinderPlus, ResFinder, and CARD. Screen isolates and metagenomes for resistance determinants. Use when characterizing resistance profiles in clinical isolates, sur...
Read, write, and create single-cell data objects using Seurat (R) and Scanpy (Python). Use for loading 10X Genomics data, importing/exporting h5ad and RDS files, creating Seurat objects and AnnData objects, and...
Perform differential expression analysis using DESeq2 in R/Bioconductor. Use for analyzing RNA-seq count data, creating DESeqDataSet objects, running the DESeq workflow, and extracting results with log fold cha...
Calculate alignment statistics including sequence identity, conservation scores, substitution matrices, and similarity metrics. Use for comparing alignment quality, measuring sequence divergence, and analyzing...
Dimensionality reduction and clustering for single-cell RNA-seq using Seurat (R) and Scanpy (Python). Use for running PCA, computing neighbors, clustering with Leiden/Louvain algorithms, generating UMAP/tSNE em...
Detect A/B compartments from Hi-C data using cooltools and eigenvector decomposition. Identify active (A) and inactive (B) chromatin compartments from contact matrices.
Create restriction maps showing enzyme cut positions on DNA sequences using Biopython Bio.Restriction. Visualize cut sites, calculate distances between sites, and generate text or graphical maps.
Visualize copy number profiles, segments, and compare across samples. Create publication-quality plots of CNV data from CNVkit, GATK, or other callers. Use when creating genome-wide CNV plots, sample heatmaps,...
Run remote BLAST searches against NCBI databases using Biopython Bio.Blast. Use for sequence similarity searches, identifying unknown sequences, finding homologs, and querying NCBI's nr/nt databases.
Deep learning-based variant calling with Google DeepVariant. Provides high accuracy for germline SNPs and indels from Illumina, PacBio, and ONT data.
Python population genetics with scikit-allel. Read VCF files, compute allele frequencies, calculate diversity statistics, perform PCA, and run selection scans using GenotypeArray and HaplotypeArray data structu...
Perform geometric calculations on protein structures using Biopython Bio.PDB. Use for measuring distances, angles, and dihedrals, finding neighbor atoms, superimposing structures, calculating RMSD, identifying...
Detect signatures of natural selection using Fst, Tajima's D, iHS, XP-EHH, and other selection statistics. Calculate population differentiation, test for departures from neutrality, and identify selective sweep...
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