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- Click a Taxonomic data node
- Choose Choose taxonomic level from the Metagenomic section of the toolbox
- Check one or more taxonomic levels. The options are Superkingdom, Kingdom, Phylum, Class, Order, Family, Genus, or Species (Figure 1). A separate output data node will be generated for each one that is selected (Figure 2)
- Click Finish
The choice of taxonomic level depends on which level you want to perform downstream analysis on and your research question. For example, if you want to know which families of bacteria are the most abundant in your sample, choose the family level. If you want to see which species are differentially abundant in different groups of samples, choose the species level.
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SubtitleText | Choose taxonomic level task set up page. Check one or more boxes |
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AnchorName | Choose taxonomic level task set up |
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![](/download/attachments/19335520/Choose%20taxonomic%20level.png?version=1&modificationDate=1624546422960&api=v2)
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SubtitleText | One output data node is produced for each taxonomic level chosen |
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AnchorName | Choose taxonomic level output |
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Download a count matrix
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SubtitleText | Download the matrix of read counts for each taxon per sample |
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AnchorName | Download count matrix |
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SubtitleText | Example of Phylum-level count matrix with features (phyla) on columns. Column 1 is the sample name. Columns 2 & 3 are sample attributes. Columns 4+ are different phyla. The counts re are the number of reads that have been classified for each phylum, for each sample |
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AnchorName | Phylum-level count matrix |
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![](/download/attachments/19335520/Example_phylum_counts.png?version=1&modificationDate=1624616386799&api=v2)
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The taxon-level count data node(s) behave like any other count matrix in Partek Flow. This means you can perform most of the tasks you would normally perform on gene expression data. For example, you can normalize the species counts, perform principal components analysis (PCA), and use ANOVA to detect differentially abundant species in different groups of samples (Figure 5). Additional visualizations can also be generated including heatmaps, volcano plots, dot plots, and more.
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