Platform

Our flagship genomics sequencing platform represents the pinnacle of GPU-accelerated bioinformatics innovation, employing cutting-edge NVIDIA Parabricks algorithms engineered for clinical-grade genomic analysis. We deliver comprehensive whole genome sequencing (WGS) and whole exome sequencing (WES) workflows with unparalleled computational efficiency and analytical precision. The platform seamlessly integrates multi-omics data from Illumina NovaSeq, PacBio HiFi, and Oxford Nanopore MinION/PromethION platforms, processing over 1TB of high-throughput sequencing data daily while maintaining clinical-grade accuracy.In addition to DNA sequencing, our platform offers advanced RNA sequencing (RNA-seq) analysis for transcriptome profiling, gene expression quantification, and alternative splicing detection. Leveraging GPU-accelerated alignment and quantification tools, we support bulk and single-cell RNA-seq workflows, enabling rapid and accurate identification of differentially expressed genes, fusion transcripts, and isoform diversity across diverse biological samples. Our RNA-seq pipelines are compatible with 10x Genomics, Illumina, and Oxford Nanopore platforms, providing end-to-end solutions from raw data processing to functional annotation and pathway analysis.

Our cutting-edge spatial transcriptomics platform delivers unprecedented spatially-resolved single-cell RNA sequencing analysis with integrated histopathological context across diverse tissue architectures. Utilizing advanced computational algorithms for 10x Genomics Visium, Slide-seq v2, and emerging spatial technologies including STARmap and MERFISH, we provide comprehensive spatial gene expression profiling with sub-cellular resolution. Our proprietary tissue deconvolution algorithms achieve 98.1% accuracy in spatial gene expression quantification while seamlessly integrating H&E staining, immunofluorescence, and multiplexed protein analysis for comprehensive molecular cartography. The platform supports automated spot detection, spatial clustering, and cell-type annotation using deep learning models trained on large-scale spatial datasets. Interactive visualization tools enable researchers to explore gene expression patterns in situ, correlate molecular signatures with tissue morphology, and identify spatially distinct cellular niches. Multi-modal data integration combines transcriptomic, proteomic, and imaging data for holistic tissue analysis.

Our sophisticated drug repurposing platform leverages comprehensive transcriptomic signature analysis, network pharmacology, and AI-driven hypothesis generation to identify novel therapeutic applications for existing FDA-approved compounds and investigational drugs. By integrating large-scale datasets from the Connectivity Map (CMAP L1000), LINCS L1000, Drug Signatures Database, and Open Targets, we systematically analyze differential gene expression profiles from over 1.3 million perturbation experiments, enabling the discovery of inverse disease-drug connectivity patterns and mechanistic insights. The platform employs advanced machine learning algorithms—including random forests, graph neural networks, and deep autoencoders—to correlate disease signatures with drug-induced transcriptomic changes, prioritize candidate compounds, and predict off-target effects. Network-based approaches map drug-disease associations through protein-protein interaction networks, pathway enrichment, and systems biology models, uncovering hidden relationships and polypharmacology opportunities.

The platform supports comprehensive tumor profiling, including detection of single nucleotide variants (SNVs), insertions/deletions (InDels), copy number variations (CNVs), and gene fusions, enabling precise characterization of tumor heterogeneity and clonal evolution. Integrated RNA-seq workflows provide insights into gene expression changes, alternative splicing events, and immune microenvironment signatures, supporting immunotherapy biomarker discovery and patient stratification. Our liquid biopsy solutions utilize next-generation sequencing (NGS) and digital PCR for non-invasive monitoring of ctDNA, allowing real-time assessment of tumor burden, treatment resistance, and disease progression. Automated bioinformatics pipelines ensure accurate variant annotation, interpretation, and reporting in compliance with FDA and CAP/CLIA guidelines. The platform offers actionable clinical reporting with therapeutic matching for targeted therapies, immunotherapies, and clinical trial enrollment, leveraging curated knowledge bases such as OncoKB, CIViC, and COSMIC. Advanced analytics modules provide tumor mutation burden (TMB), microsatellite instability (MSI), homologous recombination deficiency (HRD), and other key biomarkers to guide precision medicine decisions.