Output

gene_info

• summary.txt Lists the main assembly metrics (i.e. numbers as well as mean, SD, min and max of length, GC content and coverage) on contig and gene level
• raw_gene_table.csv Contains all variables with values as they have been computed on the input data set (for detailed description of each variable, see this section
• imputed_gene_table.csv The same as raw_gene_table.txt|.csv except for the variables 'c_genecovsd', 'c_genelensd', 'g_covdev_c', 'g_gcdev_c', 'g_lendev_c' which are rescaled to a range of 0 to 1 NaN (= missing) values are imputed with the mean of the respective variable

taxonomic_assignment

The label in the plots, which represents the query species, is automatically determined and always colored in a dark grey

• 3D_plot.html Interactive 3D scatterplot to examine genes and their taxonomic assignments
  • with single-clicks on labels you can hide individual groups
  • double-clicks hide every group except for the one that was clicked
  • hovering over data points shows additional information
  • the subdirectory “3D_plot_files” holds additional files for this plot and is required to display the plot (important when working with MobaXterm for example)
• gene_table_taxon_assignment.csv raw_gene_table with PCA coordinates for each gene and their taxonomic assignment appended
  • this is a tabular representation of all information that is displayed in the 3D plot
  • see Additional information for details on the contained information
• taxsun.tsv Input file to explore the taxonomic assignment of the genes with taxSun

PCA

• contribution_of_variables.png|.pdf Figure illustrating how much each variable contributes to the first two principal components
• genes_and_variables.png|.pdf Biplot of variables (vectors) and genes (points) in the new coordinate system defined by the first two principal components. Transparency represents the amount of contribution to the principal components
• pca_loadings.csv Table listing the loadings of the original variables (rows) on the computed principal components (columns)
• pca_summary.csv Table listing standard deviation, proportion of explained variance and cumulative proportion of explained variance in the original data for each of the principal components
• scree_plot.png|.pdf Scree plot visualising the amount of variance in the original data that is explained by each of the principal components (here: dimensions)
• parallel_analysis.png|.pdf Only available if parallel analysis was performed on the principal components. Results of Horn’s parallel analysis: plotting random eigenvalues for the given number of PCs, adjusted and unadjusted eigenvalues, indicating which one were retained for the subsequent PCA

taxonomic_hits.txt

This file is the output of DIAMOND and holds the exact hits for each protein. The columns are the following:

• qseqid Query Sequence ID (equal column fasta_header in 'gene_table_taxon_assignment.csv')
• sseqid Subject Sequence ID - accession number of the matched protein in DB
• pident Percentage of identical matches
• length Alignment length
• mismatch Number of mismatches
• gapopen Number of gap openings
• qstart Start of alignment in query
• qend End of alignment in query
• sstart Start of alignment in subject
• send End of alignment in subject
• evalue Expect value
• bitscore Bit score
• staxids Unique Subject Taxonomy ID(s), separated by a ’;’ (in numerical order)
• ssciname Unique Subject Scientific Name(s), separated by a ';'