Author: Jakub M Bartoszewicz; Anja Seidel; Bernhard Y Renard
Title: Interpretable detection of novel human viruses from genome sequencing data Document date: 2020_1_30
ID: ac00tai9_21
Snippet: Similarily to Zhang et al. (2019) , we used the human blood DNA virome dataset (Moustafa et al., 2017) to test the selected classifiers on real data. We obtained 14,242,329 reads of 150bp and searched all of VHDB using blastn (with default parameters) to obtain high-quality reference labels. If a read's best hit was a human-infecting virus, we assigned it to a positive class; the negative class was assigned if this was not the case. This procedur.....
Document: Similarily to Zhang et al. (2019) , we used the human blood DNA virome dataset (Moustafa et al., 2017) to test the selected classifiers on real data. We obtained 14,242,329 reads of 150bp and searched all of VHDB using blastn (with default parameters) to obtain high-quality reference labels. If a read's best hit was a human-infecting virus, we assigned it to a positive class; the negative class was assigned if this was not the case. This procedure yielded 14,012,665 "positive" and 229,664 "negative" reads.
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