Summary

Basic Descriptive Statistics
! Data Leakage
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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 transcription_factor_prediction_mouse_1_val.csv.gz against train set transcription_factor_prediction_mouse_1_train.csv.gz
Data Leakage:!WarningHow a flag is decided →
gb-qc v1.0.0 · run 2026-09-15 22:30:52

Basic Descriptive Statistics

Filename transcription_factor_prediction_mouse_1_val.csv.gz transcription_factor_prediction_mouse_1_train.csv.gz
Number of sequences 6745 53952
Minimum length 101 101
Mean length 101.00 101.00
Maximum length 101 101
!

Data Leakage

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 transcription_factor_prediction_mouse_1_val.csv.gz transcription_factor_prediction_mouse_1_train.csv.gz
Data Leakage (percentage) 0.16% 0.03%
Data Leakage (count) 11 15
Similarity Histogram
16 high-similarity alignments
Query (Q) Target (T) Q Cov. T Cov. % Identity % Similarity E-value Alignment
seq_2701_test seq_24830_train 0.98 0.98 95.9 93.98 8.81e-44
seq_2701_test seq_12871_train 1.00 0.98 94.0 92.12 8.03e-41
seq_2888_test seq_2666_train 0.99 0.99 93.0 92.07 1.60e-39
seq_288_test seq_20139_train 0.98 0.98 93.9 92.02 1.70e-40
seq_4241_test seq_30715_train 0.98 0.98 93.9 92.02 1.70e-40
seq_2701_test seq_26290_train 0.95 0.95 96.8 91.96 1.89e-43
seq_2701_test seq_25437_train 0.94 0.94 96.8 91.09 8.65e-43
seq_2701_test seq_27261_train 0.97 0.97 93.8 90.99 7.59e-40
seq_2558_test seq_22045_train 0.97 0.98 92.9 90.11 1.36e-37
seq_6512_test seq_41446_train 1.00 0.99 91.0 90.09 1.09e-35
seq_3802_test seq_1393_train 0.98 0.98 91.9 90.06 2.84e-37
seq_3405_test seq_18204_train 0.98 0.98 91.9 90.06 2.84e-37
seq_6287_test seq_2666_train 0.96 0.96 93.8 90.05 3.37e-39
seq_6061_test seq_43317_train 0.96 0.96 93.8 90.05 3.37e-39
seq_1628_test seq_6614_train 0.96 0.96 93.8 90.05 3.37e-39
seq_2701_test seq_3413_train 0.97 0.97 92.8 90.02 3.11e-38