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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 enhancer_promoter_interaction_GM12878_test.csv.gz against train set enhancer_promoter_interaction_GM12878_train.csv.gz
Data Leakage:!WarningHow a flag is decided →
gb-qc v1.0.0 · run 2026-09-15 22:31:34

Basic Descriptive Statistics

Filename enhancer_promoter_interaction_GM12878_test.csv.gz enhancer_promoter_interaction_GM12878_train.csv.gz
Number of sequences 2000 10000
Minimum length 5000 5000
Mean length 5000.00 5000.00
Maximum length 5000 5000

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 enhancer_promoter_interaction_GM12878_test.csv.gz enhancer_promoter_interaction_GM12878_train.csv.gz
Data Leakage (percentage) 0.90% 0.18%
Data Leakage (count) 18 18
Similarity Histogram
18 high-similarity alignments
Query (Q) Target (T) Q Cov. T Cov. % Identity % Similarity E-value Alignment
seq_165_test seq_8093_train 0.99 0.99 99.5 98.50 0.00e+00
seq_1980_test seq_5647_train 0.99 0.99 99.4 98.41 0.00e+00
seq_1838_test seq_3167_train 0.99 0.99 99.4 98.41 0.00e+00
seq_552_test seq_3000_train 0.99 0.99 99.4 98.41 0.00e+00
seq_1023_test seq_1120_train 0.99 0.99 99.4 98.41 0.00e+00
seq_1066_test seq_715_train 0.99 0.99 99.4 98.41 0.00e+00
seq_1873_test seq_1635_train 0.99 0.99 99.4 98.41 0.00e+00
seq_1651_test seq_1870_train 0.99 0.99 99.4 98.41 0.00e+00
seq_31_test seq_301_train 0.99 0.99 99.4 98.41 0.00e+00
seq_1133_test seq_4230_train 0.99 0.99 99.4 98.41 0.00e+00
seq_1166_test seq_2971_train 0.99 0.99 99.4 98.41 0.00e+00
seq_801_test seq_2665_train 0.99 0.99 99.4 98.41 0.00e+00
seq_892_test seq_1032_train 0.99 0.99 99.4 98.41 0.00e+00
seq_1161_test seq_6641_train 0.99 0.99 99.3 98.31 0.00e+00
seq_1854_test seq_4967_train 0.99 0.99 99.3 98.31 0.00e+00
seq_1186_test seq_2506_train 0.99 0.99 99.2 98.21 0.00e+00
seq_807_test seq_9777_train 0.99 1.00 99.0 98.01 0.00e+00
seq_1335_test seq_6152_train 0.95 0.95 98.2 93.29 0.00e+00