Overview
Purna is a variant analysis and genomic interpretation platform designed for research and clinical workflows. It provides a comprehensive framework for genomic data management and analysis — enabling you to identify and classify genetic variants, annotate them with evidence from curated databases, and generate actionable insights. The platform integrates raw genetic data with relevant patient metadata and applies validated pipelines for annotation, classification, and interpretation. It compiles publicly available datasets, laboratory-specific data, and community-curated evidence to produce comprehensive, custom genetic reports that support clinical decision-making and research activities.Purna is a research and clinical decision-support tool. All outputs are intended to assist qualified professionals and should be reviewed by a genetic specialist before being used in any clinical context.
Intended users
Purna is built for laboratories, hospitals, and organizations specializing in genetic analysis, interpretation, and reporting. The platform is designed for use by genetic specialists — including clinical geneticists, genetic counselors, molecular biologists, and bioinformaticians — with advanced expertise in genomics and variant interpretation.Intended population
Purna is intended for use on genomic data obtained from individuals undergoing genetic testing across a range of clinical and research contexts, including diagnostic testing, carrier screening, predictive testing, and pharmacogenomic analysis.Specimen types
Purna operates on processed genomic sequence data derived from human biological specimens. The platform does not handle physical samples directly. It requires sequence data (VCF files, or FastQ and BAM files for enterprise customers) that originate from specimens such as:- Whole blood
- Cord blood
- Dried blood spots
- Saliva swabs
- Cultured fibroblasts
- Frozen tissues
- Buccal swabs
- Other biological specimens yielding extractable DNA
Operating principles
Purna operates by processing and interpreting next-generation sequencing (NGS) data derived from human biological specimens. The platform uses validated bioinformatics pipelines to detect, annotate, and classify genetic variants.Data ingestion
Upload VCF files in GRCh37 (hg19) or GRCh38 (hg38) format. The platform auto-detects the genome assembly and validates the input.
Annotation
Variants are annotated using Ensembl VEP with RefSeq transcripts, population frequencies from gnomAD, clinical classifications from ClinVar, and in silico predictions from SIFT, PolyPhen-2, and AlphaMissense. See the Annotation Pipeline for full technical details.
Classification
Each variant receives an automated ACMG/AMP pathogenicity classification based on 28 standard criteria. Classifications can be refined interactively using AI-enhanced evidence gathering from multiple databases.
Supported applications
The platform is compatible with data generated from the following sequencing technologies:| Application | Description |
|---|---|
| Whole Exome Sequencing (WES) | Coding regions of the genome, typically 30,000–100,000 variants |
| Whole Genome Sequencing (WGS) | Full genome coverage, up to 1 million variants (enterprise for larger datasets) |
| Targeted gene panels | Custom or curated gene sets, typically 100–5,000 variants |
| Chromosomal Microarray Analysis (CMA) | Copy number variant detection from array-based platforms |
Nature of output
Purna delivers qualitative, semi-quantitative, and quantitative outputs to support genetic data interpretation:Variant annotations
Variant annotations
Each variant is annotated with HGVS nomenclature, consequence terms, transcript information, genomic coordinates, and dbSNP identifiers. Full annotation details are described in the Annotation Pipeline.
Pathogenicity classifications
Pathogenicity classifications
Automated ACMG/AMP classifications (Pathogenic, Likely Pathogenic, VUS, Likely Benign, Benign) with per-criterion evidence. Classifications can be reviewed and reclassified manually or with AI Enhance.
Population frequencies
Population frequencies
Global and population-specific allele frequencies from gnomAD, including maximum population frequency and homozygote counts.
In silico predictions
In silico predictions
Functional impact predictions from SIFT, PolyPhen-2, and AlphaMissense with numeric scores and categorical predictions.
Clinical database cross-references
Clinical database cross-references
ClinVar clinical significance, review status, associated conditions, and accession identifiers.
Phenotype matching
Phenotype matching
HPO-based phenotype-to-gene matching with match scores and rankings using Phen2Gene integration.
Clinical reports
Clinical reports
Structured reports including variant interpretation, clinical findings, case summaries, ACMG evidence, and variant comparisons. See Clinical Reports.
Custom analysis outputs
Custom analysis outputs
Tables, statistical results, and publication-quality visualizations generated through Code Execution using Python or R.
Data sources
Purna integrates evidence from the following public databases. All sources are updated on a regular schedule to reflect the latest available data.| Database | Category | Used For |
|---|---|---|
| ClinVar | Clinical | Variant clinical significance, review status, conditions |
| gnomAD | Population | Allele frequencies across global populations |
| OMIM | Clinical | Gene-disease relationships and inheritance patterns |
| PubMed | Literature | Peer-reviewed publications and case reports |
| Ensembl VEP | Annotation | Consequence prediction, transcript mapping, HGVS |
| RefSeq | Annotation | Transcript definitions and gene models |
| AlphaMissense | Prediction | Deep learning-based missense pathogenicity |
| SIFT | Prediction | Sequence homology-based functional impact |
| PolyPhen-2 | Prediction | Structure and sequence-based functional impact |
| dbSNP | Identifiers | Variant rsID identifiers |
| ClinGen | Clinical | Gene-disease validity and dosage sensitivity |
| Orphanet | Clinical | Rare disease classifications and epidemiology |
| PharmGKB | Pharmacogenomics | Drug-gene interactions and dosing guidelines |
Limitations
- Purna is a decision-support tool. It does not make autonomous clinical decisions and is not intended to replace the judgment of qualified genetic specialists.
- Automated ACMG/AMP classifications are rule-based starting points. All classifications should be reviewed by a trained professional before being used in a clinical setting.
- Variant annotations reflect the versions of reference databases at the time of processing. Re-annotation may be needed as databases are updated.
- The platform currently supports Single Inherited Disease case types. Family Inherited Disease and Somatic case types are coming soon.
Security and privacy
- All data is encrypted in transit (TLS) and at rest.
- Patient data is stored in your organization’s isolated environment and is never shared across accounts.
- Access to individual cases is controlled through role-based permissions configurable in Team settings.
Never include patient-identifying information such as names, medical record numbers, or contact details in case names, notes, or shared conversations. Use anonymized identifiers for all cases.