herry423/bionexus-reliability
Scientific Reliability Layer for AI-Assisted Biology. Know what your evidence actually warrants: pre-submission shadow review of multi-donor single-cell differential expression, evidence gap location, and human scientific review support.
Audit completed results from literature, database, analysis, sequence, structure, or slide capabilities, then optionally assemble an explicitly adjudicated multi-source claim assessment. Passive only; never select tools, infer evidence relationships, or make the final scientific decision.
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV using native allotropy or declarative YAML mapping rules. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis.
Prepare nf-core samplesheets, cluster nextflow.config, and write launch artifacts. nfcore_launch.py only wraps nf-core/rnaseq and nf-core/scrnaseq with optional nextflow -preview. Other pipelines still use generate_samplesheet.py plus a hand-written nextflow run. Does not reimplement the pipelines.
SHA-256 hashes, environment snapshot, and activity-aware Methods text. Use to attach a reproducibility sidecar to an analysis. Do not use for 21 CFR Part 11, GxP, ALCOA+, or CLIA audit claims.
This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".
Train official scvi-tools models (scVI/scANVI/totalVI/PeakVI/MultiVI/veloVI) on raw counts after the scRNA gold chain. Use for probabilistic batch integration or those named models. Does not run DestVI/Cell2location. Do not log-normalize before setup_anndata.
Review completed multi-donor single-cell differential expression before submission. Accept existing DE tables, sample sheets, AnnData, scripts and claims; produce located findings, evidence gaps, repairs and human review. Record pilot observations without claiming validated benefit.
scverse scRNA gold chain on .h5ad/.h5 — inspect, convert, MAD QC, optional scanpy.pp.scrublet, preprocess, Harmony/ComBat, PCA-UMAP-Leiden, Wilcoxon markers, subset, pseudobulk, pydeseq2, stable plots. Use when the user has scRNA-seq counts. Does not assign cell-type labels. rank_genes_groups is not condition DE. Do not call local doublet/ambient helpers SoupX, CellBender, or scDblFinder.
squidpy spatial gold chain on SpatialData .zarr or AnnData .h5ad with obsm['spatial']. Use when the user has Visium/Slide-seq/generic spots or cells with coordinates. Builds a knn spatial graph, Moran SVGs, and spatial_scatter plots. Multi-table SpatialData requires --table. Does not run Cell2location, BayesSpace, SpaGCN, or vendor HD/Xenium pipelines. Numeric clusters only.
Orient a session on this plugin. BioNexus is a Scientific Reliability Layer for AI-Assisted Biology. Route completed single-cell DE to the pre-submission shadow review; check backend readiness before a requested analysis. Do not assign cell-type labels or run analyses from this skill.