Skill UI

Query NCBI ClinVar for variant clinical significance, mixing gene/condition searches, API/FTP downloads, and VCF annotations to support genomic medicine interpretation workflows.

Integrate with the DNAnexus cloud genomics platform to build apps/applets, manage FASTQ/BAM/VCF data, run workflows, and script automations via dxpy for biomedical pipelines.

Pysam offers Python bindings to htslib for reading and writing SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences, enabling coverage stats, pileup analysis, variant queries, and seamless integration into NGS pipelines.

TileDB-VCF lets you ingest, store, query, and export large genomic VCF/BCF datasets using TileDB’s sparse arrays, supporting incremental sample growth, parallel regions queries, and cloud-local interoperability for population genomics workflows.

High-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames. Supports overlap, nearest, merge, coverage, complement and subtract for BED/VCF/BAM/GFF files, with streaming and cloud-native access as a faster bioframe alternative.

A Python library for reading, querying, filtering, and writing genomic file formats including SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, and tabix data. Supports pileup, coverage analysis, indexing, and CRAM reference operations with HTSlib integration. Ideal for bioinformatics workflows requiring low-level streaming access to genomic data.

Store and query genomic variant data with TileDB sparse arrays. Ingest VCF/BCF files, add samples incrementally, run parallel region queries, and export subsets for population genomics workflows.

Converts genomic intervals across BED, GFF/GTF, VCF, SAM/BAM, WIG and other conventions, normalizes and compares variant representations, and detects assembly or contig-naming mismatches before they corrupt an analysis.

This skill provides a comprehensive framework for academic writers aiming to submit manuscripts to specialized international economics and trade journals. It helps users assess their paper's alignment with the target journal's scope, key research themes (e.g., open economy, GVCs, cross-border e-commerce), required methodology (e.g., empirical models, international comparability), and structural standards. It is crucial for preventing manuscript rejection due to scope mismatch or formatting errors.

This comprehensive skill provides a detailed guide and heuristic checklist for authors targeting the Journal of International Trade. It helps users evaluate their manuscript's fit across multiple dimensions, including open economy focus, empirical methodology, global value chain analysis, and trade policy relevance. It serves as a crucial pre-submission tool to optimize structure and increase the chances of acceptance in top international economics journals.

This guide provides essential knowledge for selecting and defending data sources for advanced research in international economics. It emphasizes the critical need for data to possess a 'global attribute,' covering trade flows, Global Value Chains (GVC), and cross-country comparisons. Key data types include micro-level customs data (firm-product-destination), cross-country panels (WDI, IMF), and global input-output tables (WIOD/ADB MRIO) for GVC decomposition.

This comprehensive guide details professional standards for presenting complex empirical economic results (tables and figures) for top-tier journals like The Journal of World Economy. It instructs users on simplifying main regression tables, standardizing notes (clustering, significance), and correctly presenting specialized open-economy objects such as event studies, gravity regressions, and GVC decompositions, ensuring research meets publication quality.