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Hosted & Self-Serve

We run it.
You get results.

The Agent Platform is EdGeneAI's hosted motion — subscription or API access to AI agents that handle your entire RNA-Seq workflow, end to end, on our infrastructure.

Request a Pilot → Looking for licensed Skills instead?

Four agents. One pipeline. Zero bottlenecks.

Each agent is purpose-built for a specific stage of RNA-Seq analysis — working autonomously, in sequence, handing off results automatically.

AGENT 01
🔬

RNA-Seq QC & Preprocessing Agent

Ingests raw FASTQ files, runs comprehensive quality control, detects contamination and batch effects, and outputs clean, analysis-ready data.

FastQCMultiQCTrimmomaticBatch Detection
AGENT 02
📊

Differential Expression & Pathway Agent

Runs DESeq2/edgeR automatically, performs pathway enrichment across KEGG, GO, and Reactome, and produces AI-powered biological interpretation.

DESeq2edgeRKEGGVolcano Plots
AGENT 03
🧬

Single-Cell RNA-Seq Agent

End-to-end scRNA-Seq analysis: cell clustering, trajectory inference, cell-type identification, and cell-cell communication.

SeuratScanpyUMAPCellChat
AGENT 04
🔭

Long-Read RNA Variant Calling Agent

Built for ONT and PacBio long-read RNA-Seq. Detects fusion genes, novel isoforms, structural variants, and SNVs.

ONTPacBioFusion DetectionIsoforms
Agent 01 — Quality Control

RNA-Seq QC & Preprocessing

The foundation of every reliable RNA-Seq analysis — automated quality control that catches issues before they corrupt downstream results. Validated against 100+ public GEO datasets.

Per-sample and aggregate QC reports via FastQC + MultiQC
Adapter trimming and quality-based read filtering
Automated contamination and batch-effect detection
Clean output automatically passed to Agent 02
Agent 02 — Differential Expression

DE & Pathway Enrichment

The analytical core of RNA-Seq — statistical results and biological interpretation in hours, not weeks. Cross-validated against 50+ published datasets.

Differential expression with DESeq2 and edgeR, cross-validated
Pathway enrichment: KEGG, Gene Ontology, Reactome, MSigDB
Publication-ready figures — volcano, heatmap, PCA
AI-generated biological interpretation and methods section
🔒 In Development

Metagenomics agents — next on the roadmap.

The same automation approach, extended to shotgun and 16S metagenomics — taxonomic classification, diversity analysis, functional annotation, and genome assembly. We're building this deliberately, after RNA-Seq has proven itself in production. Get in touch if you'd like to be first in line when it opens.

🧫

Metagenomic QC & Preprocessing

Raw shotgun/16S read QC, host decontamination.

🦠

Taxonomic Classification & Diversity

Species/strain classification, diversity and differential abundance analysis.

🧪

Functional Annotation & AMR Detection

Functional/pathway annotation and antimicrobial resistance gene detection.

🧩

MAG Assembly & Genome Binning

Metagenome assembly, binning, and genome quality assessment.

Platform vs. manual pipeline

CapabilityManual pipelineEdGeneAI Platform
QC to DE turnaround3–6 weeks24–48 hours
ReproducibilityVariable (analyst-dependent)100% reproducible
Cross-validation (DESeq2 + edgeR)Rarely doneAlways
Biological interpretationHours of expert timeAI-generated, expert-reviewable
Scale (simultaneous projects)Limited by headcountUnlimited parallel pipelines

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