Abstract
It was with great interest that we read the recent publication by Brinkmann et al. ([1][1]) on the comparison of various methodologies for diagnosing viral infections in high-throughput sequencing (HTS) data sets. The authors demonstrated that there is a plethora of workflows and pipelines available
Highlights
It was with great interest that we read the recent publication by Brinkmann et al [1] on the comparison of various methodologies for diagnosing viral infections in high-throughput sequencing (HTS) data sets
The cloud-based nature of these tools removes the requirement for users to have high-specification computers for data processing, and automated identification of microbial sequences reduces the need for any significant background in bioinformatics
We evaluated IDseq and Genome Detective against the simulated in silico data set provided by Brinkmann et al [1]
Summary
It was with great interest that we read the recent publication by Brinkmann et al [1] on the comparison of various methodologies for diagnosing viral infections in high-throughput sequencing (HTS) data sets. Several online tools, such as IDseq [2, 3] and Genome Detective [4], have recently been made available for research involving pathogen discovery and identification. The cloud-based nature of these tools removes the requirement for users to have high-specification computers for data processing, and automated identification of microbial sequences reduces the need for any significant background in bioinformatics.
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