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Predicted sponge metagenomes (KO counts) through Tax4Fun2 and PICRUSt2
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创建时间：
2021-05-14
相关数据集
Differentially abundant metabolic subsystems between microbial and viral metagenomes (mean percentage±s.e., p-values≤0.05).
Using this threshold we expect less than one false positive in the data-set. We find that viral metagenomes are significantly enriched for nucleotides and nucleosides and DNA metabolism, consistent wi
NIAID Data Ecosystem50
Example genomes and annotations.
Tab-delimited text file with one row for each of 1,020 CBB-positive and 1,020 CBB-negative microbial genomes investigated in this study. The first row is a header with column titles. The columns conta
NIAID Data Ecosystem30
Data_Sheet_1_Genome-centric view of the microbiome in a new deep-sea glass sponge species Bathydorus sp..docx
Sponges are widely distributed in the global ocean and harbor diverse symbiotic microbes with mutualistic relationships. However, sponge symbionts in the deep sea remain poorly studied at the genome l
NIAID Data Ecosystem10
Analysis of Bacterial Diversity in the Gut Microbiota of Amur Tiger and Prediction of Their Gene Functions
This study utilized high-throughput sequencing technology to analyze the diversity and predict the gene functions of gut bacteria in Amur tiger housed in two wildlife parks in Inner Mongolia Autonomou
NIAID Data Ecosystem30
Overrepresented COG groups in the MC metagenomes relative to the CT metagenomes, based on odds ratios (OR) calculated between the copy number of putative gene sequences in the MC and CT metagenomes.
aOnly those COG groups that were discussed in the present study or have been reported previously (labeled with asterisks) are shown. A full list is provided in Table S3.
NIAID Data Ecosystem20
