Results for “fastqc”

Automates sequencing quality control by running FastQC and MultiQC, extracting quality metrics, and generating publication-ready visualizations via a CLI or MCP stdio server.

Use when you need to perform quality control analysis on high-throughput sequencing data (fastq, bam, sam, or fast5 files) to identify potential problems before downstream analysis.

Use when doing lightweight FASTA/FASTQ transformations such as conversion, subsampling, subsequence extraction, trimming, or quick QC with seqtk.

Use when processing raw FASTQ files for quality control, adapter trimming, length or complexity filtering, polyG tail trimming, or generating QC reports before downstream analysis.

Use when you need to aggregate quality control reports from multiple bioinformatics tools into a single HTML report

Use when working with FASTA or FASTQ files for statistics, filtering, transformation, format conversion, searching, or set operations.

Orchestrates a complete bulk RNA-seq differential-expression study from raw FASTQ reads through QC, alignment, quantification, differential expression, pathway enrichment, and publication figures.

Fast headless browser for QA testing and site dogfooding. Navigate pages, interact with elements, verify state, diff before/after, take annotated screenshots, test responsive layouts, forms, uploads, dialogs, and capture bug evidence. Use when asked to open or test a site, verify a deployment, dogfood a user flow, or file a bug with screenshots. (gstack)

Implements OAuth 2.0/2.1 authorization flows in Fastify applications — configures authorization code with PKCE, client credentials, device flow, refresh token rotation, JWT validation, and token introspection/revocation endpoints. Use when setting up authentication, authorization, login flows, access tokens, API security, or securing Fastify routes with OAuth; also applies when troubleshooting token validation errors, mismatched redirect URIs, CSRF issues, scope problems, or RFC 6749/6750/7636/8252/8628 compliance questions.

Fast headless browser for QA testing and site dogfooding. Navigate any URL, interact with elements, verify page state, diff before/after actions, take annotated screenshots, check responsive layouts, test forms and uploads, handle dialogs, and assert element states. ~100ms per command. Use when you need to test a feature, verify a deployment, dogfood a user flow, or file a bug with evidence. Use when asked to "open in browser", "test the site", "take a screenshot", or "dogfood this". (gstack)

Fast headless browser for QA testing and site dogfooding. (gstack)

Production Fastify (TypeScript) patterns: schema validation, plugins, typed routes, error handling, security hardening, logging, testing with inject, and graceful shutdown

Profile and optimize CPU, memory, GC, and rendering performance for mobile QuizVerse.

Fine-tune Cosmos Reason video QA models using supervised fine-tuning with FSDP parallelism, including dataset preparation, spec construction, and AutoML support.

Diagnoses and resolves slow Qdrant search performance issues including high latency, low throughput, and slow filtered searches.

Guides scaling Qdrant query throughput (QPS) through performance tuning, horizontal scaling with read replicas, and disk I/O optimization.

Optimize Qdrant vector search performance through indexing strategies, query tuning, memory management, and hardware considerations.

Guides optimization of Qdrant query latency by tuning segments, memory, quantization, and search parameters.

Guide users through installing CUDA-Q, writing quantum kernels, running GPU-accelerated simulations, connecting to QPU hardware, and exploring built-in applications.

Runs a fast quality gate that detects the project stack, performs static analysis, checks cross-layer consistency, and fixes issues between pipeline phases.

Runs a structured quality control audit on codebases, covering tests, imports, static analysis, type checking, smoke tests, UI verification, file consistency, and documentation, producing a PASS/WARN/FAIL report.

Guides development of Fastify Node.js backend servers and REST APIs using TypeScript or JavaScript, covering routes, plugins, validation, error handling, authentication, testing, performance, logging, deployment, and more.

HTTP/3 and QUIC Protocol

Quickly refreshes project state when resuming work by reporting git status, recent commits, environment, memory staleness, pending tasks, and red flags.

Implements OAuth 2.0/2.1 authorization flows in Fastify applications, including authorization code with PKCE, client credentials, device flow, refresh token rotation, JWT validation, and token introspection/revocation endpoints.

Stitched Image Quality Control

Use when implementing fastapi functionality with production-grade patterns and safeguards.

Aggregate cross-asset quality control for campaigns. Use when the user requests 'run QC', 'quality check campaign', 'review all assets', or 'generate QA report'.

Build, test, inspect, install, and deploy MCP servers with FastMCP in Python, including wrapping APIs, databases, or files as tools and exposing resources or prompts.

Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.

Quick automated lint — detects common design system violations in seconds

Quick automated lint — detects common design system violations in seconds

Apache Kafka event streaming platform. Covers producers, consumers, topics, partitions, Kafka Streams, and Connect. Use for high-throughput event-driven architectures and real-time data pipelines. USE WHEN: user mentions "kafka", "event streaming", "kafka streams", "consumer groups", "topic partitions", asks about "high throughput messaging", "event sourcing", "log aggregation", "real-time pipelines" DO NOT USE FOR: simple queues - use `rabbitmq` or `activemq`; cloud-native lightweight - use `nats`; AWS-native - use `sqs`; Azure-native - use `azure-service-bus`; GCP-native - use `google-pubsub`

Provides guidance on using the QMT quantitative trading terminal, including strategy development, backtesting, and live trading for Chinese securities markets.

Provides a structured workflow for unit, integration, E2E, and performance testing, including browser automation, code review, and quality gates.