Analyze amplicon and shotgun metagenomic data with compositional-aware statistical methods.
npx skills add https://github.com/inflexa-ai/inflexa --skill microbiome
Please help me install this Agent Skill. Skill: microbiome Source: https://github.com/inflexa-ai/inflexa/tree/main/skills/microbiome Command: npx skills add https://github.com/inflexa-ai/inflexa --skill microbiome
This skill addresses the statistical pitfalls of microbiome data, such as compositionality and spurious correlations, by providing a rigorous, audit-ready pipeline for amplicon and shotgun metagenomic analysis.
Use the microbiome skill to process the demultiplexed FASTQ files in the current directory using the DADA2 pipeline and generate an ASV table.
High-intent search queries and answers about installing and using this skill.
Compositional microbiome analysis is performed using an audit-ready pipeline that processes raw FASTQ files via DADA2, calculates diversity metrics, and runs differential abundance testing using validated statistical methods like ANCOM-BC2 and ALDEx2.
To generate an ASV table from demultiplexed FASTQ files, the DADA2 pipeline is used for raw amplicon processing, producing the exact amplicon sequence variants required for downstream taxonomic profiling and ecological community assessment.
The best way to test differential abundance with covariates is using compositional-aware methods like ANCOM-BC2, ALDEx2, and MaAsLin2, which ensure statistical validity for count-based microbiome data and generate reliable, reproducible results.
Yes, DADA2 and phyloseq can be used together for 16S diversity analysis; DADA2 handles raw FASTQ processing to generate ASV tables, while phyloseq enables downstream alpha and beta diversity calculations within the R-based bioinformatics pipeline.
Compositional data requires specialized statistical methods to avoid statistical pitfalls like spurious correlations inherent in count-based microbiome data, ensuring that differential abundance testing maintains rigorous statistical validity.
Yes, you need R-based bioinformatics packages including DADA2, phyloseq, vegan, and biom-format to run shotgun metagenomic analysis, as these dependencies are required for reproducible ecological community assessment and data formatting.
KetomihineGuide single-cell analysis workflows from preprocessing to differential abundance testing.
zongtingweiAutomate amplicon microbiome workflows from raw reads to abundance summaries.
baratadiegoAnalyze species-by-site matrices with ordination, diversity, and clustering methods.
StarlitnightlyRun differential cell-type abundance analysis on single-cell AnnData between conditions.
