ai4nucleome/BioMaster

113Stars on the repository
199Mods indexed here, across every type
2mo agoLast push, which is what freshness is scored on
noneNo LICENSE: all rights reserved, so bodies are not copied

env-r-bioc

81

ai4nucleome/BioMaster

Skill OpenCode

R/Bioconductor environment for auxiliary oncology plots.

not rated 113 +1 2mo ago A 16 tokens

ai4nucleome/BioMaster

Skill OpenCode

Bulk ATAC-seq processing: assay QC gates, MACS3 fragment-aware peak calling, consensus peak matrices, differential accessibility, and motif/footprint follow-up.

not rated 113 +1 2mo ago A 42 tokens

exec-scanpy

86

ai4nucleome/BioMaster

Skill OpenCode

Run Scanpy QC, preprocessing, clustering, and annotation steps.

not rated 113 +1 2mo ago A 18 tokens

ai4nucleome/BioMaster

Skill OpenCode

Shotgun metagenomics workflow with host-depletion-aware QC, taxonomic profiling, functional profiling, AMR follow-up, and reproducible cohort-ready output tables.

not rated 113 +1 2mo ago A 39 tokens

ai4nucleome/BioMaster

Skill OpenCode

Spatially informed clustering of spatial transcriptomics data into spatial domains using GraphST (graph self-supervised contrastive learning + GNN).

not rated 113 +1 2mo ago A 34 tokens

ai4nucleome/BioMaster

Skill OpenCode

Spatial domain identification with GreS, a semantic-guided spatial representation learning framework that injects gene-level functional priors into GCN-based spot embeddings and clusters them with k-means.

not rated 113 +1 2mo ago A 44 tokens

kdense-anndata

90

ai4nucleome/BioMaster

Skill OpenCode

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

not rated 113 +1 2mo ago A 65 tokens

kdense-arboreto

91

ai4nucleome/BioMaster

Skill OpenCode

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for…

not rated 113 +1 2mo ago A 69 tokens

ai4nucleome/BioMaster

Skill OpenCode

Query the CELLxGENE Census (61M+ cells) programmatically. Use when you need expression data across tissues, diseases, or cell types from the largest curated single-cell atlas. Best for population-scale queries, reference atlas comparisons. For analyzing your own data use scanpy or scvi-tools.

not rated 113 +1 2mo ago A 69 tokens

kdense-geniml

93

ai4nucleome/BioMaster

Skill OpenCode

This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file…

not rated 113 +1 2mo ago A 91 tokens

ai4nucleome/BioMaster

Skill OpenCode

Use when the user is doing AI/ML work in a scientific domain — biology, chemistry, physics, astronomy, climate, genomics, materials science, medicine, ecology, energy, conservation, engineering, mathematics, scientific reasoning, drug discovery, protein design, weather modeling, theorem proving, single-cell, PDE…

not rated 113 +1 2mo ago A 283 tokens

kdense-lamindb

95

ai4nucleome/BioMaster

Skill OpenCode

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological…

not rated 113 +1 2mo ago A 138 tokens

kdense-scanpy

96

ai4nucleome/BioMaster

Skill OpenCode

Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use…

not rated 113 +1 2mo ago A 71 tokens

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