ECOLE: Learning to call copy number variants on whole exome sequencing data.

Copy number variants (CNV) are shown to contribute to the etiology of several genetic disorders. Accurate detection of CNVs on whole exome sequencing (WES) data has been a long sought-after goal for use in clinics. This was not possible despite recent improvements in performance because algorithms mostly suffer from low precision and even lower recall on expert-curated gold standard call sets. Here, we present a deep learning-based somatic and germline CNV caller for WES data, named ECOLE. Based on a variant of the transformer architecture, the model learns to call CNVs per exon, using high-confidence calls made on matched WGS samples. We further train and fine-tune the model with a small set of expert calls via transfer learning. We show that ECOLE achieves high performance on human expert labelled data for the first time with 68.7% precision and 49.6% recall. This corresponds to precision and recall improvements of 18.7% and 30.8% over the next best-performing methods, respectively. We also show that the same fine-tuning strategy using tumor samples enables ECOLE to detect RT-qPCR-validated variations in bladder cancer samples without the need for a control sample. ECOLE is available at https://github.com/ciceklab/ECOLE .

Is sarcoidosis related to metabolic syndrome and insulin resistance?

Aim: To investigate the relationship between sarcoidosis and metabolic syndrome (MetS) and insulin resistance (IR).Method: In our study, 47 patients with sarcoidosis who applied to our outpatient clinic and 45 healthy individuals without chronic disease were included. All patients were evaluated for MetS according to the National Cholesterol Education Program's Adult Treatment Panel III (NCEP-ATP III) criteria. The presence of three of the five factors defined by ATP III for MetS was accepted as a diagnosis of MetS. IR is calculated using the HOMA-IR index.Results: The mean age of the 47 patients with sarcoidosis was 50.7 ± 12.2 years and the mean age of the 45 control groups was 42.9 ± 14.4 years. Almost 80% of the patients were diagnosed as stage 2 sarcoidosis. Distribution of the patients according to the use of steroid is; almost half of the patients (47%) received steroid previously or recently. Patients with sarcoidosis have a 7.66 relative risk for MetS, whereas they also have a 5.48 relative risk of insulin resistance development.Conclusion: This study shows that MetS is associated with increased sarcoidosis risk. MetS and IR diagnosis was higher in patients with sarcoidosis.