Build interactive HTML/web visualizations with plotly (Python/R), bokeh (Python), and gganimate/plotly frames for animation, with awareness of current Kaleido static-export model…
Build publication-quality figures with matplotlib using the object-oriented Figure/Axes API, constrained_layout, rcParams customization, TrueType (Type-42) font embedding for…
Compose multi-panel publication figures with patchwork, cowplot, gridExtra (R), or matplotlib GridSpec/subfigures (Python) including shared axes/legends/guides collection, panel…
Extract, filter, annotate, and export differential expression results from DESeq2 or edgeR. Use for identifying significant genes, applying multiple testing corrections — from…
Handles batch effects in bulk RNA-seq via design-matrix inclusion (the correct path for DE), ComBat/ComBat-seq for visualization, SVA for unknown latent factors, RUVSeq for…
Extracts, filters, annotates, and exports differential expression results from DESeq2 or edgeR with proper handling of padj=NA (independent filtering, Cook's outliers, all-zero),…
Performs differential expression on bulk RNA-seq count data with DESeq2's negative-binomial GLM, Wald and LRT testing, apeglm/ashr/normal LFC shrinkage, independent filtering,…
Analyzes species-environment relationships with constrained ordination (CCA, RDA, db-RDA), variance partitioning, indicator species (indicspecies IndVal.g group-equalized),…
Retrieve records from NCBI databases using Biopython Bio.Entrez (EFetch, ESummary). Use when downloading sequences, fetching GenBank/GenPept records, getting document sum — from…
Find cross-database references between NCBI databases using Biopython Bio.Entrez (ELink). Use when navigating gene to protein/structure, sequence to publication, PubMed to GEO,…
Normalizes and transforms RNA-seq count matrices for DE, visualization, clustering, and ML. Covers between-sample (TMM, TMMwsp, RLE/median-of-ratios, upper quartile),…
Work with FASTQ quality scores using Biopython. Use when analyzing read quality, filtering by quality, trimming low-quality bases, or generating quality reports.
Work with FASTQ quality scores using Biopython. Use when analyzing read quality, filtering by quality, trimming low-quality bases, or generating quality reports.
Filter and select sequences by criteria (length, ID, GC content, patterns) using Biopython. Use when subsetting sequences, removing unwanted records, or selecting by spec — from…
Filter and select sequences by criteria (length, ID, GC content, patterns) using Biopython. Use when subsetting sequences, removing unwanted records, or selecting by spec — from…
Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces.
Compare gene co-expression and regulatory networks between biological conditions to find rewired relationships using DiffCorr, DiffCoEx, DINGO/iDINGO, and CoDiNA.
MS-DIAL-based metabolomics preprocessing as alternative to XCMS. Covers peak detection, alignment, annotation, and export for downstream analysis.
MS-DIAL-based metabolomics preprocessing as alternative to XCMS. Covers peak detection, alignment, annotation, and export for downstream analysis.
Visualize metagenomic profiles using R (phyloseq, microbiome) and Python (matplotlib, seaborn). Create stacked bar plots, heatmaps, PCA plots, and diversity analyses.
Alpha and beta diversity analysis for microbiome data. Calculate within-sample richness, evenness, and between-sample dissimilarity with phyloseq and vegan.
Alpha and beta diversity analysis for microbiome data. Calculate within-sample richness, evenness, and between-sample dissimilarity with phyloseq and vegan.
Handle paired-end FASTQ files (R1/R2) using Biopython. Use when working with Illumina paired reads, synchronizing pairs, interleaving/deinterleaving, or filtering paired — from…
Handle paired-end FASTQ files (R1/R2) using Biopython. Use when working with Illumina paired reads, synchronizing pairs, interleaving/deinterleaving, or filtering paired — from…
Parse and write protein structure files using Biopython Bio.PDB. Use when reading PDB, mmCIF, and MMTF files, downloading structures from RCSB PDB, or writing structures — from…
Parse and write protein structure files using Biopython Bio.PDB. Use when reading PDB, mmCIF, and MMTF files, downloading structures from RCSB PDB, or writing structures — from…
Modify protein structures using Biopython Bio.PDB. Use when transforming coordinates, removing atoms or residues, adding new entities, modifying B-factors and occupancies — from…
Modify protein structures using Biopython Bio.PDB. Use when transforming coordinates, removing atoms or residues, adding new entities, modifying B-factors and occupancies — from…
Navigate protein structure hierarchy using Biopython Bio.PDB SMCRA model. Use when accessing models, chains, residues, and atoms, iterating over structure levels, or extr — from…
Navigate protein structure hierarchy using Biopython Bio.PDB SMCRA model. Use when accessing models, chains, residues, and atoms, iterating over structure levels, or extr — from…
Compute evolutionary distances and build phylogenetic trees using Biopython Bio.Phylo.TreeConstruction.
Build maximum likelihood phylogenetic trees using IQ-TREE2 and RAxML-NG with expert model selection, branch support assessment, and topology testing.
Read, write, and convert phylogenetic tree files using Biopython Bio.Phylo. Use when parsing Newick, Nexus, PhyloXML, or NeXML tree formats, converting between formats, o — from…
Modify phylogenetic tree structure using Biopython Bio.Phylo. Use when rooting trees with outgroups, midpoint, or MAD methods, pruning taxa, collapsing clades, ladderizin — from…
Draw and export phylogenetic trees using Biopython Bio.Phylo with matplotlib and modern alternatives.
Genome-wide association studies (GWAS) with PLINK. Perform case-control and quantitative trait association testing using logistic/linear regression with covariates, gener — from…
Read biological sequence files (FASTA, FASTQ, GenBank, EMBL, ABI, SFF) using Biopython Bio.SeqIO. Use when parsing sequence files, iterating multi-sequence files, random — from…
Read biological sequence files (FASTA, FASTQ, GenBank, EMBL, ABI, SFF) using Biopython Bio.SeqIO. Use when parsing sequence files, iterating multi-sequence files, random — from…
Build reproducible scientific documents, presentations, and websites with Quarto supporting R, Python, Julia, and Observable JS.
Select restriction enzymes by criteria using Biopython Bio.Restriction. Find enzymes that cut once, don't cut, produce specific overhangs, are commercially available, or — from…
Create restriction maps showing enzyme cut positions on DNA sequences using Biopython Bio.Restriction.
Find restriction enzyme cut sites in DNA sequences using Biopython Bio.Restriction. Search with single enzymes, batches of enzymes, or commercially available enzyme sets — from…
Generate reverse complements and complements of DNA/RNA sequences using Biopython. Use when working with opposite strands, primer design, or converting between template a — from…
Create and manipulate Seq, MutableSeq, and SeqRecord objects using Biopython. Use when creating sequences from strings, modifying sequence data in-place, or building anno — from…
Slice, extract, and concatenate biological sequences using Biopython. Use when extracting subsequences, joining sequences, or manipulating sequence regions by position.
Dimensionality reduction and clustering for single-cell RNA-seq using Seurat (R) and Scanpy (Python).
Dimensionality reduction and clustering for single-cell RNA-seq using Seurat (R) and Scanpy (Python).
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 — from…
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 — from…
Detect and remove doublets (multiple cells captured in one droplet) from single-cell RNA-seq data. Uses Scrublet (Python), DoubletFinder (R), and scDblFinder (R).
Find marker genes and annotate cell types in single-cell RNA-seq using Seurat (R) and Scanpy (Python).
Find marker genes and annotate cell types in single-cell RNA-seq using Seurat (R) and Scanpy (Python).
Quality control, filtering, and normalization for single-cell RNA-seq using Seurat (R) and Scanpy (Python).
Quality control, filtering, and normalization for single-cell RNA-seq using Seurat (R) and Scanpy (Python).
Discovers periodic signals of unknown period in time-series omics data using Lomb-Scargle periodograms (scipy), autocorrelation, and wavelet time-frequency decomposition (pywt).
End-to-end 16S amplicon workflow from FASTQ reads to differential abundance. Orchestrates DADA2 ASV inference, taxonomy assignment, diversity analysis, and compositional — from…
Write biological sequences to files (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO. Use when saving sequences, creating new sequence files, or outputting modifie — from…
Write biological sequences to files (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO. Use when saving sequences, creating new sequence files, or outputting modifie — from…
Use when applying Biome's linting capabilities, rule categories, and code quality enforcement to JavaScript/TypeScript projects.
Biopython is a comprehensive set of freely available Python tools for biological computation. It provides functionality for sequence manipulation, file I/O, database access,…