The reference dataset for this species has substantial quality issues. Thresholds should be treated as indicative only.
Derived from 8 genomes: 4 from RefSeq and 4 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 1 genome at PASS, 0 at WARN, and 26 at FAIL (27 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 | 4 | 305,298 | 129,113 | 176,185 | 176,185 | 305,298 | 434,410 | 434,410 |
| no_of_contigs | insufficient_data | 4 | 55.25 | 21.75 | 33 | 33.75 | 55.5 | 77 | 77 |
| longest | insufficient_data | 4 | 637,281 | 175,703 | 461,578 | 461,578 | 637,281 | 812,983 | 812,983 |
| GC_Content | insufficient_data | 4 | 53.3 | 0.04 | 53.27 | 53.27 | 53.3 | 53.34 | 53.34 |
| Completeness_Specific | insufficient_data | 4 | 100 | 0 | 100 | 100 | 100 | 100 | 100 |
| Contamination | insufficient_data | 4 | 1.28 | 0.39 | 0.89 | 0.89 | 1.28 | 1.67 | 1.67 |
| Total_Coding_Sequences | insufficient_data | 4 | 5,864 | 83.25 | 5,780 | 5,781 | 5,864 | 5,947 | 5,947 |
| Genome_Size | insufficient_data | 4 | 6,273,678 | 42,697 | 6,230,971 | 6,230,986 | 6,273,666 | 6,316,358 | 6,316,409 |
Full statistics including KS test vs RefSeq and Wasserstein distance are in the downloadable summary.csv.
Derived from 8 genomes including 4 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 | 6,200,000 | 6,200,000 | 6,400,000 | 6,400,000 |
| GC_Content | 53.2 | 53.2 | 53.4 | 53.4 |
| Total_Coding_Sequences | 5,700 | 5,700 | 6,000 | 6,000 |
| Completeness_Specific | 100 | 100 | - | - |
| Contamination | - | - | 2 | 2 |
| N50 | 176,000 | 176,000 | - | - |
| no_of_contigs | - | - | 80 | 80 |
| 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 huaxiensis 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 huaxiensis 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.