Improving the Accuracy of Base Calls and Error Predictions for GS 20 DNA Sequence Data
نویسنده
چکیده
New DNA sequencing technology implemented in the GS 20 sequencer reduces cost and time in exchange for lower accuracy. DNA sequencing errors negatively impact downstream applications and therefore accurate base calls and error probabilities are invaluable to researchers. This paper applies a graphical model to the base calling problem in context of the GS 20 sequencer. This model integrates signal information from the local sequence neighborhood to generate calls within a probabilistic framework. Results indicate improved accuracy for base calls early in the sequence process, but the overall perforance decreases.
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