Selected article for: "posterior probability distribution and probability distribution"
Author: Jiao Chen; Jiayu Shang; Jianrong Wang; Yanni Sun
Title: A binning tool to reconstruct viral haplotypes from assembled contigs
  • Document date: 2019_7_16
    • ID: 2basllfv_25
    Snippet: The clustering algorithm will assign each sub-contig to one cluster based on the posterior probability of the abundance distribution. Although . CC-BY-NC-ND 4.0 International license The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a . https://doi.org/10.1101/704288 doi: bioRxiv preprint different clustering methods such as Gaussian mixture model can be applied to cluster the su.....
    Document: The clustering algorithm will assign each sub-contig to one cluster based on the posterior probability of the abundance distribution. Although . CC-BY-NC-ND 4.0 International license The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a . https://doi.org/10.1101/704288 doi: bioRxiv preprint different clustering methods such as Gaussian mixture model can be applied to cluster the sub-contigs, the augmented K-means as shown below has the fastest convergence with better clustering accuracy according to our tests. Before we describe the main components, we first introduce the notations. The average relative abundance (denote asc) for a sub-contig c i in a window of depth N is calculated as:

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