Total 30,738 skills, Data Processing has 1471 skills
Showing 12 of 1471 skills
Use this skill for AIRR-seq (Adaptive Immune Receptor Repertoire / VDJ-seq) data analysis with immunarch + immundata in R, including ingestion, receptor schema design, immutable transformations, clonality/diversity/public overlap metrics, and Seurat/AnnData integration.
Google BigQuery for analytics, ML, and data warehousing. Use for large-scale analytics.
TimescaleDB PostgreSQL for time-series. Use for time-series on Postgres.
SQL database queries, joins, aggregations, subqueries, and optimization. Use for .sql files and database operations.
Plotly interactive visualization library. Use for interactive charts.
Apache Spark distributed computing. Use for big data processing.
Use this skill for AIRR-seq (Adaptive Immune Receptor Repertoire / VDJ-seq) data analysis with immunarch + immundata in R, including ingestion, receptor schema design, immutable transformations, clonality/diversity/public overlap metrics, and Seurat/AnnData integration.
Real-time analytics with Redis counters, periodic PostgreSQL flush, and time-series aggregation. High-performance event tracking without database bottlenecks.
Centralized transformation logic for consistent data shaping across API routes. Includes aggregators, rankers, trend calculators, and data sanitizers.
Exactly-once processing semantics with distributed coordination for file-based data pipelines. Atomic file claiming, status tracking, and automatic retry with in-memory fallback.
Daily compression of time-series data with merge logic for multiple pipeline runs, structured aggregation for dashboards, and storage estimation for capacity planning.
Use when extracting entities and relationships, building ontologies, compressing large graphs, or analyzing knowledge structures - provides structural equivalence-based compression achieving 57-95% size reduction, k-bisimulation summarization, categorical quotient constructions, and metagraph hierarchical modeling with scale-invariant properties. Supports recursive refinement through graph topology metrics including |R|/|E| ratios and automorphism analysis.