Genomic Data Test
Genomic Data Test
Primary & Secondary analyses pipeline
Version 1
Genomic raw data are processing using Dragen hardware.
Pre-Aggregation QC pipeline
Version 1
This pipeline tests each WGS sample, independently. If a sample fails this test, then it is excluded from the aggregation and not released or reported in this document. These tests detect sample swaps, cross-individual contamination, and sample preparation/sequencing errors. The list of specific QC processes is listed in the table below:
Aggregation Pipeline
Version 1
Samples that PASS the pre-aggregation QC pipeline (per sample QC) are aggregated into one multi-sample VCF file. Sample are aggregated using Dragen Iterative gVCF genotyper. To accelerate the aggregation and the downstream analyses (parallel processing), the genome is split into 100 shards.
The output of this pipeline is a multi-sample VCF. One multi-sample VCF is generated per shard in addition to the global multi-sample VCF files (all shards concatenated).
120. An ensemble-based machine learning model for predicting type 2 diabetes and its effect on bone health
Belqes Alsadi, Saleh Musleh, Hamada R. H. Al-Absi, Mahmoud Refaee, Rizwan Qureshi, Nady El Hajj & Tanvir Alam
119. Using nephropathy as an outcome to determine the HbA1c diagnostic threshold for type 2 diabetes
Alexandra E. Butler a,*, Steven C. Hunt b,c,1, Eric S. Kilpatrick
118. Predicted deleterious variants in the human genome relevant to gene therapy with adeno-associated virus vectors
Mahboubeh R. Rostami, Philip L. Leopold, Jenifer M. Vasquez, Miguel de Mulder Rougvie, Alya Al Shakaki, Ali Ait Hssain, Amal Robay, Neil R. Hackett, Jason G. Mezey, Ronald G. Crystal
117. DNAJB3 attenuates ER stress through direct interaction with AKT
Zeyaul IslamID , Abdoulaye Diane, Namat Khattab, Mohammed Dehbi, Paul Thornalley, Prasanna R. Kolatkar
116. Multi-disease Retinal Vessel Segmentation: A Deep Learning Approach
Mohammad Tariqul Islam; Hesham Zaky; Tanvir Alam
115. DiaNet v2 deep learning based method for diabetes diagnosis using retinal images
Hamada R. H. Al-Absi, Anant Pai, Usman Naeem, Fatma Kassem Mohamed, Saket Arya, Rami Abu Sbeit, Mohammed Bashir, Maha Mohammed El Shafei, Nady El Hajj & Tanvir Alam