Project name: Influenza A virus strain:A/Puerto Rico/8/1934(H1N1) and A/WSN/33(H1N1)

Description: With next generation sequencing technologies, it is now feasible to efficiently sequence patient-derived samples at a depth of coverage sufficient to detect rare genotypic variants. However, each sequencing platform has characteristic error profiles, and sample collection, target amplification, and library preparation are additional processes whereby errors are introduced and propagated. Many studies account for these errors by using ad hoc quality thresholds and/or previously published statistical algorithms. Despite common usage, the majority of these approaches have not been validated under conditions that characterize many studies of intrahost diversity. In order to determine the accuracy of these approaches we made defined populations of influenza virus which mimicked the diversity and titer typically found in patient-derived samples. We identified single nucleotide variants using two commonly used variant callers, DeepSNV and LoFreq, and found that the accuracy of these variant callers was lower than expected and exquisitely sensitive to input titer. Here we provide the raw data so that others may test there own methods on real, and relevant viral sequences.

Data type: raw sequence reads

Sample scope: Multiisolate

Relevance: Evolution

Last updated: 2016-04-07