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Intelli-NGS: Intelligent NGS, a deep neural network-based artificial intelligence to delineate good and bad variant calls from IonTorrent sequencer data

Aditya SinghiD, Prateek BhatiaiD

Abstract

BackgroundIonTorrent is a second-generation sequencing platform with smaller capital costs than Illumina but is also prone to higher machine error than later. Given its lower costs, the platform is generally preferred in developing countries where next-generation sequencing is still a very exclusive technique. There are many software tools available for other platforms but IonTorrent. This makes the already tricky analysis part more error-prone. MotivationWe have been using the IonTorrent platform in our hospital setting for aiding diagnosis or treatment for the past couple of years. Given to our experience, analysis part of IonTorrent data takes the longest time and still, we used to get stuck with certain variants which seemed fine on looking at their metrics but were found to be negative in Sanger sequencing verification. This made us determined to develop a tool that could aid us in reducing false positive and negative rates while still retaining good recall. The artificial intelligence-based technique was our final choice after developing pipelines with less success. MethodologyThe artificial intelligence was developed from scratch in Python 3 using TensorFlow fully connected dense layers. The model takes VCF files as input and solves each variant based on the thirty-five parameters given by the IonTorrent platform, including the flow-space information which is missed by variant callers other than the default torrent variant caller. ResultsThe final trained model was able to achieve an accuracy of 93.08% and a ROC-AUC of 0.95 with GIAB validation data. The additional program that was written to run the model annotates each variant using online databases such as dbSNP, ClinVar and others. A probability score for each outcome for each variant is also provided to aid in decision making. AvailabilityThe model and running code are available for free only for non-commercial users at https://www.github.com/aditya-88/intelli-ngs.

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