Execute single-cell ATAC-seq pipelines from fragment import to motif enrichment.
npx skills add https://github.com/Minions-Land/AutOmicScience --skill omics-scatac
Please help me install this Agent Skill. Skill: omics-scatac Source: https://github.com/Minions-Land/AutOmicScience/tree/main/skills/omics/scatac Command: npx skills add https://github.com/Minions-Land/AutOmicScience --skill omics-scatac
This skill addresses the complexity of single-cell chromatin accessibility analysis by providing a reproducible, evidence-based pipeline that prevents common bioinformatics pitfalls like technical confounding and hallucinated results.
Use the omics-scatac skill to perform quality control and peak calling on the provided fragments file for a single-cell ATAC-seq experiment.
High-intent search queries and answers about installing and using this skill.
Single-cell ATAC-seq quality control and peak calling can be executed by importing fragment files to run TSS enrichment, doublet filtering, and peak calling using snapATAC2 and MACS3.
Identifying cell-type-specific enhancers from 10x scATAC-seq data involves orchestrating a workflow from fragment import to peak-gene linkage and motif enrichment, recording every tool call as evidence.
Cross-modality integration with scRNA-seq references is supported for scATAC-seq chromatin accessibility data, enabling comparative analysis between gene activity estimation and reference transcriptomes.
pychromVAR works with snapATAC2 within a pinned scverse environment to perform motif activity analysis and identify potential regulatory elements in single-cell ATAC-seq pipelines.
Technical confounding in single-cell chromatin accessibility analysis is prevented by applying rigorous fragment-size distribution analysis, TSS enrichment, and doublet filtering during the automated processing pipeline.
A pinned scverse environment is required for single-cell ATAC-seq analysis to ensure reproducible and grounded scientific results by maintaining strict version control over snapATAC2, MACS3, and pychromVAR dependencies.
KetomihineOrganize, query, and visualize spatial omics data with a unified Python framework.
ya-wayAnalyze single-cell ATAC-seq data to identify regulatory elements and cell types.
mkurmanOrganize annotated single-cell data with a flexible AnnData structure.
CHENyiru3Integrate scATAC-seq chromatin accessibility analysis with Seurat workflows.
