Identifying Gut Microbiota Associated With Colorectal Cancer Using a Zero-Inflated Lognormal Model

In this study, we identified the differentially abundant gut microbes between CRC and healthy samples using the Ratio Approach for Identifying Differential Abundance (RAIDA) algorithm (Sohn et al., 2015). The algorithm fitted the distribution of observed data with a modified zero-inflated lognormal (ZIL) model and estimated the statistical significance of abundance difference by the T-test. Furthermore, we used the GRAMMy algorithm (Xia et al., 2011) to estimate and analyze the relative abundance of gut microbes and diversity of the microbial communities. Finally, we constructed and analyzed a microbial association network based on all healthy, small adenoma, large adenoma, and CRC samples. Materials and Methods Two Metagenomics Datasets Our first gut metagenomics dataset was downloaded from the European Nucleotide Archive (ENA) database (accession number ERP005534) (Table 1). The dataset (Zeller et al., 2014) consists of 156 samples from France (61 healthy, 27 small adenoma, 15 large adenoma, and 53 CRC samples). Samples with an adenoma diameter smaller than 10 mm were classified as small adenoma while those with larger than 10 mm ones were classified as large adenoma. TABLE 1 Table 1. Number of experimental samples. Our second gut metagenomics dataset was also downloaded from the ENA database (accession number ERP008729) (Zeller et al., 2014). The dataset included 156 samples from Austria, including 63 healthy samples, 47 adenoma patient samples, and 46 CR...
Source: Frontiers in Microbiology - Category: Microbiology Source Type: research

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