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Fig. 1 | BMC Genomics

Fig. 1

From: Frequentmers - a novel way to look at metagenomic next generation sequencing data and an application in detecting liver cirrhosis

Fig. 1

Visualization of frequenter extraction pipeline and inference. Two groups of samples are examined, the first group is composed of healthy control samples and serves as the control and the second group contains patient samples, for the disease that is investigated. mNGS data are analyzed to determine the number of kmers found in each sample and subsequently the kmers unique to only one group (healthy controls or patients) are identified. Frequentmers represent the recurrent kmers found only in patient samples or only in healthy control samples, but never in both. Frequentmers that are found in multiple samples of only one group are used as features to train a machine learning algorithm to perform binary classification on unseen data

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BMC Genomics

ISSN: 1471-2164

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