academic
3
risk-of-bias
Assess risk of bias in research studies for systematic reviews. Use when: (1) Conducting systematic reviews, (2) Evaluating study quality, (3) GRADE assessments, (4) Meta-analysis planning.
astoreyai
research
sorting
stars
current ordering strategy
query
all entries
refine the visible subset
academic
3
inclusion-criteria
Apply inclusion/exclusion criteria systematically in literature reviews. Use when: (1) Screening abstracts, (2) Reviewing full texts, (3) Documenting screening decisions, (4) Ensuring PRISMA compliance.
astoreyai
research
academic
3
parallel-search
使用多組關鍵字並行搜尋，提高文獻覆蓋率。觸發：並行搜尋、parallel search、批量搜尋、擴展搜尋、多組搜尋、同時搜、找更多、廣泛搜尋、comprehensive search。
u9401066
research
scientific-computing
3
research-patterns
Research methodology and best practices for finding existing patterns
akaszubski
research
academic
3
policyengine-analysis
Common analysis patterns for PolicyEngine research repositories (CRFB, newsletters, dashboards, impact studies)
PolicyEngine
research
bioinformatics
3
policyengine-uk-data
UK survey data enhancement - FRS with WAS imputation patterns
PolicyEngine
research
bioinformatics
3
hic-tad-calling
This skill should be used when users need to identify topologically associating domains (TADs) from Hi-C data in .mcools (or .cool) files or when users want to visualize the TAD in target genome loci. It provides workflows for TAD calling and visualization.
BIsnake2001
research
scientific-computing
3
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. Use this skill when you have filtered and generated the clean BAM file (e.g. `*.filtered.bam`).
BIsnake2001
research
scientific-computing
3
atacseq-qc
Performs ATAC-specific biological validation. It calculates metrics unique to chromatin accessibility assays, such as TSS enrichment scores and fragment size distributions (nucleosome banding patterns). Use this skill when you have filtered BAM file and have called peak for the file. Do NOT use this skill for ChIP-seq data or general alignment statistics.
BIsnake2001
research
bioinformatics
3
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.
BIsnake2001
research
scientific-computing
3
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.
BIsnake2001
research
bioinformatics
3
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.
BIsnake2001
research
bioinformatics
3
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.
BIsnake2001
research
bioinformatics
3
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.
BIsnake2001
research
scientific-computing
3
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.
BIsnake2001
research
bioinformatics
3
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.
BIsnake2001
research
bioinformatics
3
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.
BIsnake2001
research
scientific-computing
3
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.
BIsnake2001
research
scientific-computing
3
peak-calling
Perform peak calling for ChIP-seq or ATAC-seq data using MACS2, with intelligent parameter detection from user feedback. Use it when you want to call peaks for ChIP-seq data or ATAC-seq data.
BIsnake2001
research
scientific-computing
3
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.
BIsnake2001
research
bioinformatics
3
shader-sdf
Signed Distance Functions (SDFs) in GLSL—2D/3D shape primitives, boolean operations (union, intersection, subtraction), smooth blending, repetition, and raymarching fundamentals. Use when creating procedural shapes, text effects, smooth morphing, or raymarched 3D scenes.
Bbeierle12
research
scientific-computing
3
genomic-feature-annotation
This skill is used to perform genomic feature annotation and visualization for any file containing genomic region information using Homer (Hypergeometric Optimization of Motif EnRichment). It annotates regions such as promoters, exons, introns, intergenic regions, and TSS proximity, and generates visual summaries of feature distributions.
BIsnake2001
research
bioinformatics
3
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.
BIsnake2001
research