Clostridium cagae is an anaerobic, Gram-positive, spore-forming rod of the family Clostridiaceae, isolated from human faecal samples. It is a commensal member of the human gut microbiota and has not been prominently associated with clinical disease, though its ecology within the intestinal community is not yet fully characterised. Genomically, C. cagae possesses a moderately sized genome typical of gut-associated clostridia, with genes related to complex polysaccharide degradation and short-chain fatty acid production.
The thresholds for this species may be unreliable due to a low number of reference genomes included in the analysis.
For detailed methods on how these thresholds were calculated, please see Methods. The suggested thresholds are in the table below. These thresholds are based on 0 genomes from RefSeq and 107 genomes from other sources.
These tables provide a summary of the distribution of each metric, including SDeviation, Mean, Median, and Percentiles.
These thresholds were applied to all the bacteria dataset. 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.
| Metric | Lower bound | Upper bound |
|---|---|---|
| N50 | 26,000 | - |
| no_of_contigs | - | 300.0 |
| GC_Content | 27.00 | 27.00 |
| Completeness | 99.00 | - |
| Contamination | - | 1.000 |
| Total_Coding_Sequences | 3,300 | 4,000 |
| Genome_Size | 3,600,000 | 4,100,000 |
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 genome size increases, the number of coding sequences should also increase. Any secondary trend lines or non-linear behaviour indicates bona fide separate populations within the retained genomes or some remaining contaminant.
A table of complete RefSeq genomes for Clostridium cagae used to calibrate this scheme. The file includes accessions, some sample information, genome size, GC content, and other key metrics.
These plots show genomes before and after filtering to highlight the outliers removed. Left: Heatmap of all genomes in the dataset. Middle: A representative sample of genomes, with anomalies highlighted (purple). Right: The filtered distribution after applying filtering. There may have been additional adjustments and rounding so the distribution here may not enirely match with the final suggested metrics.
