Manipulate biological sequences and perform bioinformatics analyses in Python.
npx skills add https://github.com/rubensliv/k-dense-ai --skill scikit-bio-rubensliv
Please help me install this Agent Skill. Skill: scikit-bio Source: https://github.com/rubensliv/k-dense-ai/tree/main/scientific-skills/scikit-bio Command: npx skills add https://github.com/rubensliv/k-dense-ai --skill scikit-bio-rubensliv
scikit-bio provides a unified, high-performance Python library for working with biological data, enabling sequence manipulation, alignment, phylogenetics, microbial ecology analyses, and multivariate statistics.
Install scikit-bio and begin processing sequences with DNA.read on a FASTA file to perform basic manipulations.
High-intent search queries and answers about installing and using this skill.
To calculate alpha and beta diversity metrics, the library provides built-in functions for UniFrac and PCoA ordination methods. These operate on biological data tables to extract ecological diversity insights directly.
You can read and write FASTA and FASTQ files for sequence analysis in Python. The library handles biological format I/O, enabling sequence manipulation like reverse-complement, transcription, and motif search.
Phylogenetic tree construction and alignment are performed using built-in pairwise and multiple sequence alignment functions, distance metrics, and tree construction tools. The library reads and writes Newick formats for tree data.
scikit-bio works with pandas and NumPy for biological data handling, providing full interoperability. This allows seamless integration of biological format parsing with multivariate statistical analysis workflows.
You parse BIOM tables and distance matrices for microbial ecology analyses using the library's dedicated file I/O handlers. This enables direct loading of biological data formats for downstream ordination and diversity workflows.
Ordination methods like PCoA are needed for ecological datasets to visualize beta diversity and distance matrices. These multivariate techniques summarize biological data variation, revealing patterns in high-dimensional microbiome samples.
jackspaceAnalyze biological sequences for microbiome and ecological data interpretation.
ya-wayRead, manipulate, and analyze biological sequences in FASTA, FASTQ, and GenBank formats.
Zeyuyang-0420Analyze biological sequences, alignments, phylogenetic trees, and diversity metrics with scikit-bio.
SologaAnalyze biological data with sequence manipulation, alignment, and statistical testing.
