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Illumina

  • Type: Analyze
  • Analyze: kraken2
  • Classifier: V-SEARCH
  • Sample : test-merge-illumina

Result: includes 3 : taxa-bar-plots, taxomy tree with read, result folder. User have to input parameters into input box (Database sequence), it would be show basic information and logs:

  • Classify (taxonomy)

New Evaluate:

  • Number of threads: this index on normal computer can: 16, 30
  • Number of reads sub sampled: the smaller is faster (default)
  • Clustering similarity threshold: the smaller the value the faster

All stages have 2 stages after processing: compress and update if 1 of both is failed, it is considered run fail.

  1. Taxa-bar-plots

    Taxa-bar-plots creates a taxa bar chart from the data frame

    plot_tax_bar(

    taxa_df,

    rank,

    colours = NULL,

    sample = "X SampleID",

Rank is the taxonomic rank at which to view the data. Must be one of ‘Genus’,’Family’,’Order’,’Class’, ‘Phylum’. Colour is accommodate all your taxa at the appropriate rank.

Sample: the name of the sample column in the data frame.

Abound: the name of the abundance column in the data frame.

Tax_df: the data frame used for plotting.

Bar width refers to the width of the bars in a bar chart. In the bar chart. In a bar chart, data is represented by rectangular bars with lengths proportional to the values they represent. The width of these bars can vary depending on the design and configuration of the chart. Bar width is an important aspect of bar charts because it affects the visual clarity and interpretation of the data. If the bar are too narrow, it may be difficult to distinguish between them, especially when there are many bars or when the differences in values are small. On the other hand, if the bars are too wide, they may overlap or take up too much space, reducing the overall readability of the chart. Adjusting the bar width allows you to control the balance between the amount of detail and the overall clarity of the chart.

Taxonomic level refers to the hierarchical classification of organisms based on their shared characteristics and evolutionary, the encompass many different to specific group that contain closely related species. Taxonomic levels provide a systematic framework for organizing and categorizing the diversity of life on Earth, allowing scientists to study and understand the relationship between different organisms.

  1. Taxomy tree with read

You can select each level, to see the series.

The higher the level, the more visible and complex the chart. We can choose the percentage display to increase and decrease the numbers of baches displayed. At each point when selected, the name, numbers of read, numbers of creatures in the samples will be displayed

In the expand will list the species groups displayed such as: Root, Bacteria, Cyanobacteria, Firmicutes, Actinobacteriota, proteobacteria, Myxococcota, Uncultured,…. And it will display numbers of read

  1. Result folder

In result folder includes: results and three file data of sample. In results have 5 file:

  • File classified: classified-sequence-fasta: classified-seq.fasta

Clustering similarity threshold Rep-seq.qza: is a file containing clustered sequens

Reports: report.tsv: is a file containing information about the sequence

Unclassified: sign to identify processing the result is: unclassified-seq.fasta

Sign to identify the finished sorting stage: merge.csv

Sign that identify the stage of processing the result: result.txt

And three files: merged.fasta, mered.fastq.gz, taxonomy_tree_with_read.json.

+) File taxonomy_tree_read.json: is file containing information data

+) 2 files merged.fasta, mered.fastq.gz: is file containing information of processing the result