The reference dataset for this species has substantial quality issues. Thresholds should be treated as indicative only.
Derived from 12 genomes: 6 from RefSeq and 6 from other sources. For the derivation pipeline and the PASS / WARN / FAIL verdict model, see the methods page for REFSEQ-QC-v1.
Applied to the full All-The-Bacteria dataset, these thresholds place 0 genomes at PASS, 0 at WARN, and 99 at FAIL (99 assessed in total). The per-tier genome lists can be downloaded below in .csv.gz format; the FAIL list also records the reason each assembly was rejected.
This table summarises the distribution of each metric, including standard deviation, mean, median, and percentiles.
A combined summary table across all species is available on the summary page.
| Metric | Distribution | n | Mean | SD | Min | Q1 | Median | Q3 | Max |
|---|---|---|---|---|---|---|---|---|---|
| N50 | insufficient_data | 6 | 286,688 | 4,111 | 281,432 | 282,865 | 287,163 | 290,393 | 291,469 |
| no_of_contigs | insufficient_data | 6 | 50 | 5.89 | 44 | 45 | 48 | 55.5 | 58 |
| longest | insufficient_data | 6 | 677,752 | 159,764 | 551,773 | 558,407 | 578,310 | 821,957 | 903,172 |
| GC_Content | insufficient_data | 6 | 56.99 | 0.21 | 56.72 | 56.79 | 57.01 | 57.18 | 57.23 |
| Completeness_Specific | insufficient_data | 6 | 100 | 0 | 100 | 100 | 100 | 100 | 100 |
| Contamination | insufficient_data | 6 | 0.07 | 0.02 | 0.04 | 0.05 | 0.08 | 0.09 | 0.09 |
| Total_Coding_Sequences | insufficient_data | 6 | 4,944 | 87.29 | 4,821 | 4,864 | 4,992 | 5,012 | 5,018 |
| Genome_Size | insufficient_data | 6 | 5,329,804 | 79,859 | 5,217,793 | 5,256,673 | 5,373,311 | 5,392,060 | 5,398,309 |
Full statistics including KS test vs RefSeq and Wasserstein distance are in the downloadable summary.csv.
Derived from 12 genomes including 6 RefSeq references
Both Fail and Warn bands shown as the published rounded values — easier to cite and consistent across the species page, CSV downloads, and downstream QC tools.
| Metric | Fail below | Warn below | Warn above | Fail above |
|---|---|---|---|---|
| Genome_Size | 5,200,000 | 5,200,000 | 5,400,000 | 5,400,000 |
| GC_Content | 56.7 | 56.7 | 57.3 | 57.3 |
| Total_Coding_Sequences | 4,800 | 4,800 | 5,100 | 5,100 |
| Completeness_Specific | 100 | 100 | - | - |
| Contamination | - | - | 1 | 1 |
| N50 | 281,000 | 281,000 | - | - |
| no_of_contigs | - | - | 60 | 60 |
| longest | - | - | - | - |
How to read this: a value between the two warn columns is typical for this species and passes QC. A value between a warn column and the corresponding fail column is borderline — worth a manual look but not an outright failure. A value outside the fail columns is unusual enough to fail QC.
The published rounded thresholds (the values in the table above) were applied to the full AllTheBacteria-2024-08 set for this species. Each row carries the per-metric verdict and, where applicable, the reason a genome was demoted to WARN or FAIL. Files are gzipped CSV.
This plot shows the relationship between the number of coding sequences (CDS) and genome size — how the number of genes scales with assembly length. The relationship should be roughly linear: as genome size increases, the number of coding sequences should rise proportionally. A secondary trend line or non-linear behaviour can indicate either bona fide sub-populations within the retained genomes (e.g. distinct sub-clades) or residual contamination that survived filtering.
Histogram comparing SRA to RefSeq; each bar shows genome density across value ranges to highlight shifts, peaks, or outliers.
QQ (quantile-quantile) plot comparing SRA and RefSeq. Points along the diagonal follow the expected distribution; deviations indicate skew, outliers, or other systematic differences.
A table of complete RefSeq genomes for Klebsiella africana used to calibrate this scheme. The file includes accessions, some sample information, genome size, GC content, and other key metrics.
Per-assembly inputs the engine used to derive the Klebsiella africana reference distribution for this scheme: sample, sylph species call, N50, contig count, longest contig, total length, completeness, contamination, total coding sequences, genome size, GC content. Gzipped CSV.