Predicting gene expression purely from DNA sequence has been a long-standing problem in regulatory genomics. Enformer is a novel transformer architecture that has made a significant improvement by greatly expanding the receptive field and increasing the information flow between distal elements. This model can better capture biological phenomena such as enhancers regulating promoters even though there are is large DNA sequence distance between the two. This has led to a substantial performance increase in tissue and cell-type-specific gene expression prediction correlation from 0.81 to 0.85, one third of the way towards the experimental-level accuracy of 0.94 estimated from replicates. Enformer outperformed the best team on the critical assessment of genome interpretation (CAGI5) challenge for noncoding variant interpretation with no additional training. Such advances will enable more effective fine-mapping of growing human disease associations to cell-type-specific gene regulatory mechanisms and provide a framework to interpret cis-regulatory evolution.
Input variables : DNA Sequence
Output Variables : Gene expression prediction
Statistical | : | Somers D | Accuracy | Precision and Recall | Confusion Matrix | F1 Score | Roc and Auc | Prevalence | Detection Rate | Balanced Accuracy | Cohen's Kappa | Concordance | Gini Coefficent | KS Statistic | Youden's J Index |
Business | : | Population at High Risk of Disease | Risk by Geography | Risk by Demographics | Risk by Clinical Parameters | Optimized Hospital Resource Utilization | Decreased Cost of Care | Decreased Patient Visits |
Infrastructure | : | Log Bytes | Logging/User/IAMPolicy | Logging/User/VPN | CPU Utilization | Memory Usage | Error Count | Prediction Count | Prediction Latencies | Private Endpoint Prediction Latencies | Private Endpoint Response Count |
Visit Model : github.com
Additional links : biorxiv.org
Model Category | : | Public |
Date Published | : | April, 2021 |
Healthcare Domain | : | Life Sciences |
Code | : | github.com |
Health Risk Management |
Health Risk Prediction |