obsidian-canvas
Create and manage Obsidian Canvas files with automatic layout generation. Use when creating visual knowledge maps, weekly reading summaries, or project timelines.
obsidian-cli
>-
obsidian-links
Format and validate Obsidian wiki links with proper filename, section, and folder conventions. Verify links exist before creation and fix broken links. Use when creating or checking wiki links in markdown files.
obsidian-markdown-structure
Validate and enforce markdown document structure including frontmatter positioning, heading hierarchy, and content organization. Use when creating or validating markdown files.
obsidian-mermaid
Create Obsidian-compatible Mermaid diagrams. Prefer square layouts (TB + subgraph LR), avoid markdown in labels. Use when creating flowcharts, sequence diagrams, or any Mermaid diagrams in markdown files.
obsidian-yaml-frontmatter
Manage YAML frontmatter properties with consistent formatting, property names, and value types. Use when creating or updating frontmatter in markdown files.
road-trip-planning
Create interactive HTML road-trip guides for multi-day driving itineraries. Use when an AI agent is asked to plan a road trip, build a travel itinerary page, make a fullscreen route map, estimate trip cost/time, compare restaurant or lodging alternatives, add POIs with photos and Google Maps links, or produce a self-contained HTML guide for any road trip.
video-add-chapters
Add chapters to videos by transcribing, analyzing, and generating structured markdown documents with YouTube chapter markers. Optionally generate highlight videos.
video-cleaning
Clean spoken videos by transcribing them, detecting pauses and filler words, and generating edited outputs with a conservative Korean-focused workflow.
video-full-process
Unified workflow combining video-clean and video-add-chapters with transcript reuse and chapter remapping
youtube-transcript-summarizer
Extract YouTube video transcripts and generate AI-powered summaries in any language. Converts videos to structured markdown documents with summaries, key points, and timelines.
epub-to-markdown
Convert EPUB files into a single well-formatted markdown document with extracted metadata, table of contents, and images.
gemini-image-skill
Generate document and slide images with Google Gemini or Imagen models, including style selection, aspect ratios, and approval workflow guidance.
gobi-cli
>-
gobi-migration
>-
gobi-onboarding
고비 데스크탑 3.0 대화형 음성 온보딩 가이드
interactive-writing-assistant
This skill provides comprehensive support for the writing process from ideation through revision. Use this skill when helping users write essays, articles, or creative pieces through interactive collaboration. The skill supports co-evolving outline and prose, voice-based input processing, multiple writing styles, and connection to the user's PKM system for enriched content.
markdown-slides
Create presentation slides in Markdown format (Deckset/Marp compatible). Use when user requests to create slides, presentations, or convert documents to slide format. Handles image positioning, speaker notes, and proper formatting.
markdown-video
Convert Deckset-format markdown slides with speaker notes to presentation video with TTS narration. Use when user requests to create video from slides, generate presentation video, or convert slides to MP4 format.
ai4pkm-cli
AI4PKM CLI for orchestrator configuration, worker management, vault updates, and CLI workflow integration.
create-gif-slides
Create animated GIF slideshows from structured content. Use when the user asks to create a GIF summary, animated slide recap, GIF presentation, or visual summary GIF for events, meetups, presentations, or any multi-point content. Supports Korean text, dark/light themes, custom colors, progress indicators, and quote boxes. Ideal for social media sharing (Gobi Brain Updates, Slack, etc).
docx-to-markdown
Convert DOCX files into markdown while preserving headings, lists, tables, metadata, and extracted images.
De-novo-motif-discovery
This skill identifies novel transcription factor binding motifs in the promoter regions of genes, or directly from genomic regions of interest such as ChIP-seq peaks, ATAC-seq accessible sites, or differentially acessible regions. It employs HOMER (Hypergeometric Optimization of Motif Enrichment) to detect both known and previously uncharacterized sequence motifs enriched within the supplied genomic intervals. Use the skill when you need to uncover sequence motifs enriched or want to know which TFs might regulate the target regions.
known-motif-enrichment
This skill should be used when users need to perform known motif enrichment analysis on ChIP-seq, ATAC-seq, or other genomic peak files using HOMER (Hypergeometric Optimization of Motif EnRichment). It identifies enrichment of known transcription factor binding motifs from established databases in genomic regions.
functional-enrichment
Perform GO and KEGG functional enrichment using HOMER from genomic regions (BED/narrowPeak/broadPeak) or gene lists, and produce R-based barplot/dotplot visualizations. Use this skill when you want to perform GO and KEGG functional enrichment using HOMER from genomic regions or just want to link genomic region to genes.
hic-normalization
Automatically detect and normalize Hi-C data. Only .cool or .mcool file is supported. All .mcool files are then checked for existing normalization (supports bins/weight only) and balanced if none of the normalizations exist.
local-methylation-profile
This skill analyzes the local DNA methylation profiles around target genomic regions provide by user. Use this skill when you want to vasulize the average methylation profile around target regions (e.g. TSS, CTCF peak or other target regions).
hic-compartments-calling
This skill performs PCA-based A/B compartments calling on Hi-C .mcool datasets using pre-defined MCP tools from the cooler-tools, cooltools-tools, and plot-hic-tools servers.
alignment-level-QC
Calculates technical mapping statistics for any aligned BAM file (ChIP or ATAC). It assesses the performance of the aligner itself by generating metrics on read depth, mapping quality, error rates, and read group data using samtools and Picard.Use this skill to check "how well the reads mapped" or to validate BAM formatting/sorting before further processing. Do NOT use this skill for biological signal validation (like checking for peaks or open chromatin) or for filtering/removing reads.
replicates-incorporation
This skill manages experimental reproducibility, pooling, and consensus strategies. This skill operates in two distinct modes based on the input state. (1) Pre-Peak Calling (BAM Mode): It merges all BAMs, generate the merge BAM file to prepare for track generation and (if provided with >3 biological replicates) splits them into 2 balanced "pseudo-replicates" to prepare for peak calling. (2) Post-Peak Calling (Peak Mode): If provided with peak files (only support two replicates, derived from either 2 true replicates or 2 pseudo-replicates), it performs IDR (Irreproducible Discovery Rate) analysis, filters non-reproducible peaks, and generates a final "conservative" or "optimal" consensus peak set. Trigger this skill when you need to handle more than two replicates (creating pseudo-reps) OR when you need to merge peak lists.
chromatin-state-inference
This skill should be used when users need to infer chromatin states from histone modification ChIP-seq data using chromHMM. It provides workflows for chromatin state segmentation, model training, state annotation.
UMR-LMR-PMD-detection
This pipeline performs genome-wide segmentation of CpG methylation profiles to identify Unmethylated Regions (UMRs), Low-Methylated Regions (LMRs), and Partially Methylated Domains (PMDs) using whole-genome bisulfite sequencing (WGBS) methylation calls. The pipeline provides high-resolution enhancer-like LMRs, promoter-associated UMRs, and large-scale PMDs characteristic of reprogramming, aging, or cancer methylomes, enabling integration with chromatin accessibility, TF binding, and genome architecture analyses.
differential-tad-analysis
This skill performs differential topologically associating domain (TAD) analysis using HiCExplorer's hicDifferentialTAD tool. It compares Hi-C contact matrices between two conditions based on existing TAD definitions to identify significantly altered chromatin domains.
hic-matrix-qc
This skill performs standardized quality control (QC) on Hi-C contact matrices stored in .mcool or .cool format. It computes coverage and cis/trans ratios, distance-dependent contact decay (P(s) curves), coverage uniformity, and replicate correlation at a chosen resolution using cooler and cooltools. Use it to assess whether Hi-C data are of sufficient quality for downstream analyses such as TAD calling, loop detection, and compartment analysis.
track-generation
This skill generates normalized BigWig (.bw) tracks (and/or fold-change tracks) from BAM files for ATAC-seq and ChIP-seq visualization. It handles normalization (RPM or fold-change) and Tn5 offset correction automatically. What's more, this skill can help user visualize the signal profiles around TSS or target regions. Use this skill when you have filtered and generated the clean BAM file (e.g. `*.filtered.bam`).
regulatory-community-analysis-ChIA-PET
This skill performs protein-mediated regulatory community analysis from ChIA-PET datasets and provide a way for visualizing the communities. Use this skill when you have a annotated peak file (in BED format) from ChIA-PET experiment and you want to identify the protein-mediated regulatory community according to the BED and BEDPE file from ChIA-PET.
methylation-variability-analysis
This skill provides a complete and streamlined workflow for performing methylation variability and epigenetic heterogeneity analysis from whole-genome bisulfite sequencing (WGBS) data. It is designed for researchers who want to quantify CpG-level variability across biological samples or conditions, identify highly variable CpGs (HVCs), and explore epigenetic heterogeneity.
global-methylation-profile
This skill performs genome-wide DNA methylation profiling. It supports single-sample and multi-sample workflows to compute methylation density distributions, genomic feature distribution of the methylation profile, and sample-level clustering/PCA. Use it when you want to systematically characterize global methylation patterns from WGBS or similar per-CpG methylation call files.
integrative-DMR-DEG
This skill performs correlation analysis between differential methylation and differential gene expression, identifying genes with coordinated epigenetic regulation. It provides preprocessing and integration workflows, using promoter-level methylation–expression relationships.
nested-TAD-detection
This skill detects hierarchical (nested) TAD structures from Hi-C contact maps (in .cool or mcool format) using OnTAD, starting from multi-resolution .mcool files. It extracts a user-specified chromosome and resolution, converts the data to a dense matrix, runs OnTAD, and organizes TAD calls and logs for downstream 3D genome analysis.
correlation-methylation-epiFeatures
This skill provides a complete pipeline for integrating CpG methylation data with chromatin features such as ATAC-seq signal, H3K27ac, H3K4me3, or other histone marks/TF signals.
atac-footprinting
This skill performs transcription factor (TF) footprint analysis using TOBIAS on ATAC-seq data. It corrects Tn5 sequence bias, quantifies TF occupancy at motif sites, generates footprint scores, and optionally compares differential TF binding across conditions.
peak-calling
Perform peak calling for ChIP-seq or ATAC-seq data using MACS3, with intelligent parameter detection from user feedback. Use it when you want to call peaks for ChIP-seq data or ATAC-seq data.
loop-annotation
This skill annotates chromatin loops, including enhancer/promoter assignments, CTCF-peak overlap. It automatically constructs enhancer and promoter sets when missing and outputs standardized loop categories.
hic-loop-calling
This skill performs chromatin loop detection from Hi-C .mcool files using cooltools.
BAM-filtration
Performs data cleaning and removal operations. This skill takes a raw BAM and creates a new, "clean" BAM file by actively removing artifacts: mitochondrial reads, blacklisted regions, PCR duplicates, and unmapped reads. Use this skill to "clean," "filter," or "remove bad reads" from a dataset. This is a prerequisite step before peak calling. Do NOT use this skill if you only want to view statistics without modifying the file.
differential-methylation
This skill performs differential DNA methylation analysis (DMRs and DMCs) between experimental conditions using WGBS methylation tracks (BED/BedGraph). It standardizes input files into per-sample four-column Metilene tables, constructs a merged methylation matrix, runs Metilene for DMR detection, filters the results, and generates quick visualizations.
TF-differential-binding
The TF-differential-binding pipeline performs differential transcription factor (TF) binding analysis from ChIP-seq datasets (TF peaks) using the DiffBind package in R. It identifies genomic regions where TF binding intensity significantly differs between experimental conditions (e.g., treatment vs. control, mutant vs. wild-type). Use the TF-differential-binding pipeline when you need to analyze the different function of the same TF across two or more biological conditions, cell types, or treatments using ChIP-seq data or TF binding peaks. This pipeline is ideal for studying regulatory mechanisms that underlie transcriptional differences or epigenetic responses to perturbations.
differential-region-analysis
The differential-region-analysis pipeline identifies genomic regions exhibiting significant differences in signal intensity between experimental conditions using a count-based framework and DESeq2. It supports detection of both differentially accessible regions (DARs) from open-chromatin assays (e.g., ATAC-seq, DNase-seq) and differential transcription factor (TF) binding regions from TF-centric assays (e.g., ChIP-seq, CUT&RUN, CUT&Tag). The pipeline can start from aligned BAM files or a precomputed count matrix and is suitable whenever genomic signal can be summarized as read counts per region.
hic-compartment-shift
This skill performs A/B compartment shift analysis between two Hi-C samples.
Page 1047 of 1727 · 86303 results
