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microscape

Downstream analysis toolkit for amplicon sequencing data.

microscape is a Python package and Nextflow pipeline for downstream analysis of amplicon sequencing data. It takes the output of papa2 (or any DADA2-style sequence table) and provides QC filtering, metadata integration, taxonomic renormalization, phylogenetic tree construction, ordination, co-occurrence network analysis, and visualization export.

What does microscape do?

After DADA2 denoising produces a sequence table and taxonomy assignments, microscape handles everything that comes next:

  1. Filter the sequence table by ASV length, prevalence, abundance, and sample depth
  2. Load metadata from MIMARKS-compliant sample sheets
  3. Renormalize by splitting ASVs into taxonomic groups (prokaryote, eukaryote, chloroplast, mitochondria) and computing within-group proportional abundances
  4. Build phylogeny via MAFFT multiple sequence alignment and neighbor-joining tree construction
  5. Ordinate samples using Bray-Curtis dissimilarity with t-SNE or PCA
  6. Compute networks of co-occurring ASVs using SparCC correlation
  7. Export all results as a JSON bundle for web-based visualization

Architecture

microscape has two layers:

  • Python package (microscape/) -- 8 composable functions for scripting and notebooks
  • Nextflow pipeline (nextflow/) -- reproducible, scalable execution from raw reads through visualization. DADA2 steps use papa2 for a fully Python-native amplicon workflow.

Project Layout

microscape/          Python package
  __init__.py          Public API (8 functions)
  filter.py            filter_seqtab, plot_filter_summary
  metadata.py          load_metadata
  renormalize.py       renormalize
  phylogeny.py         build_phylogeny
  ordination.py        ordinate
  network.py           sparcc_network
  viz.py               export_viz
nextflow/            Nextflow pipeline
  main.nf              Workflow orchestration
  nextflow.config      Parameters, profiles, resources
  modules/             Process definitions
  bin/                 Standalone R scripts (DADA2 steps)
  envs/                Conda environment specs
  primers/             Primer FASTA files
conda/               Bioconda recipe

Quick Smoke Test

import microscape
print(microscape.__version__)
# 0.1.0

Citation

If you use microscape in published research, please cite the original DADA2 paper:

Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP (2016). DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods, 13, 581-583. https://doi.org/10.1038/nmeth.3869

License

BSD-3-Clause -- see LICENSE.