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Clostridium cagae

This is the QualiBact page for Clostridium cagae. For detailed methods on how these thresholds were calculated, please see Methods. The suggested thresholds are:

metric lower_bounds upper_bounds
N50 26000.0
no_of_contigs 300.0
GC_Content 27.0 27.0
Completeness 99.0
Contamination 1.0
Total_Coding_Sequences 3300.0 4000.0
Genome_Size 3600000.0 4100000.0

Download metrics CSV

These thresholds are based on 0 genomes from RefSeq and 107 genomes from ATB / SRA.

These thresholds were applied to all the bacteria dataset, which resulted in removing 8 and retaining 99. The list of genomes retained (i.e. high quality) and the list of genomes rejected (filtered) can be downloaded below. These files are in .xz format. The rejected genomes file, also includes the reason why.

Download high quality genomes list

Download rejected genomes list

Summary Tables

These tables provide a summary of the distribution of each metric, including SDeviation, Mean, Median, and Percentiles.

Download full summary tables

Download simple summary tables

This plot shows the relationship between the number of coding sequences (CDS) and genome size. It helps to visualize how genome size correlates with the number of genes. This should be linear - as the genome size increases, the number of coding sequences should also increase. Any secondary trend lines or non-linear behaviour indicates bone fide seperate populations within the retained genomes, or some remaining contaminant.

CDS vs Genome Size

Illustrating the filtering process

These plots illustrate the data, pre and post filtering to demostrate what type of outliers have been removed. While this was applied to all metrics, we will demonstrate using total assembly length and N50.

N50 vs total length for all genomes in the dataset.

ALL Total Length vs N50

N50 vs total length for genomes in the dataset, coloured according to whether they are an anomaly or not.

Sampled Total Length vs N50

N50 vs total length post filtering on the dataset.

Filtered Total Length vs N50

Additional Plots

These plots provide additional insights into the genome characteristics: