「rag」の検索結果

The analysis and visualization of alternative splicing (AS) events from RNA sequencing data remains challenging. SpliceWiz is a user-friendly and performance-optimized R package for AS analysis, by processing alignment BAM files to quantify read counts across splice junctions, IRFinder-based intron retention quantitation, and supports novel splicing event identification. We introduce a novel visualization for AS using normalized coverage, thereby allowing visualization of differential AS across

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SGC is a semi-supervised pipeline for gene clustering in gene co-expression networks. SGC consists of multiple novel steps that enable the computation of highly enriched modules in an unsupervised manner. But unlike all existing frameworks, it further incorporates a novel step that leverages Gene Ontology information in a semi-supervised clustering method that further improves the quality of the computed modules.

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The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to

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The epistack package main objective is the visualizations of stacks of genomic tracks (such as, but not restricted to, ChIP-seq, ATAC-seq, DNA methyation or genomic conservation data) centered at genomic regions of interest. epistack needs three different inputs: 1) a genomic score objects, such as ChIP-seq coverage or DNA methylation values, provided as a `GRanges` (easily obtained from `bigwig` or `bam` files). 2) a list of feature of interest, such as peaks or transcription start sites, provi

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phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.

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Save MultiAssayExperiments to h5mu files supported by muon and mudata. Muon is a Python framework for multimodal omics data analysis. It uses an HDF5-based format for data storage.

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Provides efficient containers for storing and manipulating short genomic alignments (typically obtained by aligning short reads to a reference genome). This includes read counting, computing the coverage, junction detection, and working wit

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Expert knowledge for Azure Quotas development including limits & quotas. Use when requesting per-region Storage account quota increases, checking limits, or filing Azure support requests, and other Azure Quotas related development tasks. Not for Azure Cost Management (use azure-cost-management), Azure Monitor (use azure-monitor), Azure Policy (use azure-policy), Azure Resource Manager (use azure-resource-manager).

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Expert knowledge for Azure VMware Solution development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring AVS networking/storage, HCX migrations, Horizon/VDI, vSAN clusters, or Azure-integrated backups, and other Azure VMware Solution related development tasks. Not for Azure Virtual Machines (use azure-virtual-machines), Azure Stack Edge (use azure-stack-edge), Azure Nutanix (use azure-nutanix), Azure Red Hat OpenShift (use azure-redhat-openshift).

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Expert knowledge for Microsoft Foundry Classic (aka Azure AI Foundry classic) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry agents with Azure OpenAI, RAG, Azure AI Search, MCP tools, or multi-agent routing, and other Microsoft Foundry Classic related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Local (use microsoft-foundry-local), Content Safety in Foundry Control Plane (use azure-content-safety), Azure Speech in Foundry Tools (use azure-speech).

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Expert knowledge for Azure Reliability development including best practices, decision making, architecture & design patterns, limits & quotas, and deployment. Use when choosing Azure regions, availability zones, geo-paired deployments, Queue Storage limits, or Web PubSub apps, and other Azure Reliability related development tasks. Not for Azure Monitor (use azure-monitor), Azure Resiliency (use azure-resiliency), Azure Service Health (use azure-service-health), Azure Sre Agent (use azure-sre-agent).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Service Connector development including troubleshooting, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when wiring Azure compute to Redis, databases, storage, messaging, AI services, or third‑party endpoints, and other Azure Service Connector related development tasks. Not for Azure API Management (use azure-api-management), Azure Connector Namespace (use azure-connector-namespace), Azure Logic Apps (use azure-logic-apps), Azure Service Bus (use azure-service-bus).

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Expert knowledge for Azure Red Hat OpenShift development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when deploying ARO/HCP clusters, configuring networking/storage, securing with Entra/NSGs, or integrating ACR/Key Vault, and other Azure Red Hat OpenShift related development tasks. Not for Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Container Apps (use azure-container-apps), Azure Virtual Machines (use azure-virtual-machines).

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Expert knowledge for Azure Resiliency development including security, configuration, and deployment. Use when configuring resiliency drills, backup/replication policies, Recovery Plans RBAC, or Infra Resiliency Manager coverage, and other Azure Resiliency related development tasks. Not for Azure Reliability (use azure-reliability), Azure Site Recovery (use azure-site-recovery), Azure Backup (use azure-backup), Azure Monitor (use azure-monitor).

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Expert knowledge for Azure Large Instances development including troubleshooting, limits & quotas, and integrations & coding patterns. Use when configuring Epic SKUs, sizing volume groups, tuning EHR storage, or resolving Epic–ALI connectivity/perf issues, and other Azure Large Instances related development tasks. Not for Azure Baremetal Infrastructure (use azure-baremetal-infrastructure), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Machine Scale Sets (use azure-vm-scalesets), Azure HPC Cache (use azure-hpc-cache).

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Expert knowledge for Azure Managed Applications development including limits & quotas, security, configuration, and deployment. Use when designing createUiDefinition UIs, JIT access, managed identities, StorageAccountSelector, or Bicep-based catalog publishing, and other Azure Managed Applications related development tasks. Not for Azure Blueprints (use azure-blueprints), Azure Resource Manager (use azure-resource-manager), Azure Lighthouse (use azure-lighthouse), Azure Partner Solutions (use azure-partner-solutions).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure IoT Hub development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring IoT Hub/DPS routing, device twins, MQTT/AMQP clients, Device Update, or Cosmos DB event storage, and other Azure IoT Hub related development tasks. Not for Azure IoT (use azure-iot), Azure IoT Central (use azure-iot-central), Azure IoT Edge (use azure-iot-edge), Azure IoT Operations (use azure-iot-operations).

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Expert knowledge for Azure Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using AutoML, Prompt Flow, online/batch endpoints, vector stores/RAG, or MLflow/ONNX deployments, and other Azure Machine Learning related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure Data Science Virtual Machines (use azure-data-science-vm), Azure HDInsight (use azure-hdinsight).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Functions development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when wiring Functions to HTTP/storage/queues, securing with VNets/MI, tuning scaling, or deploying via CI/CD, and other Azure Functions related development tasks. Not for Azure App Service (use azure-app-service), Azure Logic Apps (use azure-logic-apps), Azure Container Apps (use azure-container-apps), Azure Kubernetes Service (AKS) (use azure-kubernetes-service).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Durable Task development including best practices, decision making, architecture & design patterns, limits & quotas, configuration, integrations & coding patterns, and deployment. Use when choosing Durable storage backends, versioning orchestrations, using fan-out/fan-in, human approvals, or instance APIs, and other Azure Durable Task related development tasks. Not for Azure Functions (use azure-functions), Azure Logic Apps (use azure-logic-apps), Azure App Service (use azure-app-service), Azure Service Fabric (use azure-service-fabric).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure HDInsight development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when working with HDInsight Spark/Hive/Kafka/HBase clusters, Ambari/Oozie pipelines, or Azure-integrated storage/BI, and other Azure HDInsight related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure Stream Analytics (use azure-stream-analytics).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Copilot development including troubleshooting, decision making, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when sizing VMs, generating Bicep/Terraform, configuring Cosmos DB chat storage, or designing Azure networks, and other Azure Copilot related development tasks. Not for Azure Portal (use azure-portal), Azure Machine Learning (use azure-machine-learning), Azure DevOps (use azure-devops), Microsoft Foundry (use microsoft-foundry).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Cloud Shell development including troubleshooting, limits & quotas, and security. Use when handling Cloud Shell storage mounts, session limits, file persistence, private VNet access, or RBAC setup, and other Azure Cloud Shell related development tasks. Not for Azure Portal (use azure-portal), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop), Azure DevOps (use azure-devops).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Content Understanding in Foundry Tools development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when building Content Understanding analyzers, RAG document flows, agentic workflows, REST/SDK calls, or GA migrations, and other Azure Content Understanding in Foundry Tools related development tasks. Not for Content Safety in Foundry Control Plane (use azure-content-safety), Azure Speech in Foundry Tools (use azure-speech), Azure AI Vision (use azure-ai-vision), Azure AI Document Intelligence (use azure-document-intelligence).

日本語の概要は準備中です。原文の説明を表示しています。