Author: Anna Shcherbina; Darrell O. Ricke; Nelson Chiu
Title: Evaluating performance of metagenomic characterization algorithms using in silico datasets generated with FASTQSim Document date: 2016_3_31
ID: csokkcqq_36
Snippet: in the algorithm calls as compared to truth, while the relative abundance of Streptococcus agalactiae 241 is higher, suggesting that a number of the reads called for S. agalactiae are actually from S. mutans 242 (Figure 3b, 3d) . This implies difficulty distinguishing between closely related species. Similarly, a high 243 number of reads are assigned correctly to the Yersinia and Escherichia genera by Kraken and 244.....
Document: in the algorithm calls as compared to truth, while the relative abundance of Streptococcus agalactiae 241 is higher, suggesting that a number of the reads called for S. agalactiae are actually from S. mutans 242 (Figure 3b, 3d) . This implies difficulty distinguishing between closely related species. Similarly, a high 243 number of reads are assigned correctly to the Yersinia and Escherichia genera by Kraken and 244
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