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Automated quality control for genomic machine learning datasets: scores the biases, duplicates and data leakage a classifier could exploit before you train on it.
Searching test set promoter_strength_leaf_test.csv.gz against train set promoter_strength_leaf_train.csv.gz
Data Leakage:!WarningHow a flag is decided →
gb-qc v1.0.0 · run 2026-09-15 22:31:29

Basic Descriptive Statistics

Filename promoter_strength_leaf_test.csv.gz promoter_strength_leaf_train.csv.gz
Number of sequences 1000 8000
Minimum length 170 170
Mean length 170.00 170.00
Maximum length 170 170

Every test sequence searched against the train set with MMseqs2, and scored on its best hit. Similarity is min(query coverage, target coverage) × percent identity: how much of the shorter sequence the alignment spans, times how much of that matches. The histogram is the distribution of those best hits.

The flag is the percentage of test sequences at or above the threshold: Pass at 0%, Warning below 2%, Fail at 2% or more. A test sequence that near-duplicates a training one is one the model has already seen, so the accuracy it earns there is not evidence. What to do about it →

The panel under the histogram lists those alignments, up to the first 100; every one of them, listed or not, is exported to mmseqs/mmseqs2_search_result.tsv beside this report. Its columns are:

Query (Q)
Identifier of the test sequence: seq_<i>_test, where i is its 0-based position in the input test file.
Target (T)
Identifier of the train sequence: seq_<i>_train, where i is its 0-based position in the input train file.
Q Cov.
Fraction of the query sequence covered by the alignment (0–1).
T Cov.
Fraction of the target sequence covered by the alignment (0–1).
% Identity
Percent identical aligned positions in the aligned region.
% Similarity
Similarity score used for leakage detection, calculated as min(Q Cov., T Cov.) × % Identity.
E-value
MMseqs2 E-value (lower is more "significant").
Alignment
Click “Show” to expand the alignment visualisation for a row.
Filename promoter_strength_leaf_test.csv.gz promoter_strength_leaf_train.csv.gz
Data Leakage (percentage) 0.70% 0.19%
Data Leakage (count) 7 15
Similarity Histogram
16 high-similarity alignments
Query (Q) Target (T) Q Cov. T Cov. % Identity % Similarity E-value Alignment
seq_355_test seq_4029_train 1.00 1.00 99.4 99.40 7.29e-90
seq_331_test seq_6686_train 1.00 0.99 95.8 95.23 1.61e-78
seq_480_test seq_1461_train 1.00 1.00 95.2 95.20 3.42e-78
seq_970_test seq_4952_train 1.00 1.00 95.2 95.20 3.42e-78
seq_479_test seq_3764_train 1.00 1.00 94.7 94.70 1.47e-76
seq_72_test seq_4952_train 0.99 0.99 95.8 94.65 1.61e-78
seq_331_test seq_2745_train 1.00 0.99 95.2 94.63 6.93e-77
seq_331_test seq_2189_train 1.00 0.99 94.7 93.56 1.39e-75
seq_331_test seq_4836_train 1.00 0.99 94.1 93.54 1.21e-73
seq_331_test seq_6272_train 1.00 0.99 94.1 93.54 2.54e-73
seq_304_test seq_2920_train 0.98 0.98 95.7 93.40 3.27e-77
seq_331_test seq_5516_train 1.00 0.99 93.5 92.38 2.33e-72
seq_331_test seq_975_train 1.00 0.99 92.9 92.34 1.92e-70
seq_331_test seq_5267_train 0.99 1.00 92.9 92.34 3.99e-70
seq_331_test seq_4353_train 1.00 0.99 92.3 91.75 7.37e-69
seq_331_test seq_7389_train 1.00 0.99 90.6 90.06 7.26e-64