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_human_1_test.csv.gz against train set transcription_factor_prediction_human_1_train.csv.gz
Data Leakage:✖FailHow a flag is decided →
gb-qc v1.0.0 · run 2026-09-15 22:30:51

Basic Descriptive Statistics

Filename transcription_factor_prediction_human_1_test.csv.gz transcription_factor_prediction_human_1_train.csv.gz
Number of sequences 1000 30672
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_human_1_test.csv.gz transcription_factor_prediction_human_1_train.csv.gz
Data Leakage (percentage) 2.90% 0.31%
Data Leakage (count) 29 94
Similarity Histogram
98 high-similarity alignments
Query (Q) Target (T) Q Cov. T Cov. % Identity % Similarity E-value Alignment
seq_865_test seq_23616_train 1.00 1.00 100.0 100.00 3.96e-52
seq_514_test seq_13016_train 0.99 0.99 100.0 99.00 1.92e-51
seq_717_test seq_4047_train 0.99 0.99 100.0 99.00 1.92e-51
seq_990_test seq_15767_train 0.99 0.99 98.0 97.02 4.83e-48
seq_865_test seq_5908_train 0.99 0.99 98.0 97.02 4.83e-48
seq_865_test seq_13010_train 0.97 0.97 100.0 97.00 4.46e-50
seq_762_test seq_5973_train 0.96 0.96 100.0 96.00 2.13e-49
seq_841_test seq_16241_train 1.00 1.00 96.0 96.00 2.34e-45
seq_841_test seq_25118_train 1.00 1.00 96.0 96.00 2.34e-45
seq_865_test seq_10701_train 0.97 0.97 98.9 95.93 2.22e-48
seq_884_test seq_26895_train 1.00 1.00 95.0 95.00 1.07e-43
seq_841_test seq_10012_train 0.98 0.98 96.9 94.96 1.08e-45
seq_841_test seq_7597_train 0.96 0.96 98.9 94.94 1.05e-47
seq_870_test seq_13224_train 1.00 0.99 95.0 94.05 2.24e-42
seq_870_test seq_21418_train 1.00 0.99 95.0 94.05 2.24e-42
seq_628_test seq_599_train 1.00 1.00 94.0 94.00 4.77e-42
seq_955_test seq_11305_train 0.98 0.97 96.9 93.99 2.33e-44
seq_990_test seq_27696_train 0.98 0.98 95.9 93.98 5.01e-44
seq_865_test seq_6496_train 0.98 0.98 95.9 93.98 5.01e-44
seq_931_test seq_19065_train 0.94 0.94 98.9 93.06 2.32e-46
seq_870_test seq_14748_train 1.00 0.99 94.0 93.06 9.67e-41
seq_684_test seq_13873_train 0.99 0.99 94.0 93.06 2.15e-41
seq_491_test seq_2719_train 0.99 0.99 94.0 93.06 2.15e-41
seq_841_test seq_17387_train 0.96 0.96 96.9 93.02 2.33e-44
seq_841_test seq_237_train 0.96 0.96 96.9 93.02 2.33e-44
seq_870_test seq_15119_train 0.98 0.97 95.9 93.02 1.05e-42
seq_586_test seq_2135_train 0.98 0.98 94.9 93.00 2.24e-42
seq_990_test seq_10097_train 0.98 0.98 94.9 93.00 2.24e-42
seq_865_test seq_28830_train 0.98 0.98 94.9 93.00 2.24e-42
seq_927_test seq_20395_train 0.98 0.98 94.9 93.00 2.24e-42
seq_628_test seq_20561_train 1.00 1.00 93.0 93.00 2.04e-40
seq_798_test seq_3657_train 0.98 0.99 94.0 92.12 4.32e-40
seq_798_test seq_27702_train 0.99 0.98 94.0 92.12 4.32e-40
seq_990_test seq_8275_train 0.99 0.99 93.0 92.07 9.10e-40
seq_865_test seq_29832_train 1.00 0.99 93.0 92.07 4.03e-39
seq_803_test seq_9447_train 0.99 0.99 93.0 92.07 9.10e-40
seq_529_test seq_5194_train 0.98 0.98 93.9 92.02 9.67e-41
seq_865_test seq_3048_train 0.98 0.98 93.9 92.02 9.67e-41
seq_529_test seq_3311_train 0.97 0.97 94.8 91.96 1.01e-41
seq_870_test seq_6002_train 0.99 0.98 93.0 91.14 1.77e-38
seq_546_test seq_9181_train 0.98 0.99 93.0 91.14 1.77e-38
seq_841_test seq_28202_train 0.94 0.94 96.8 91.09 4.92e-43
seq_675_test seq_8082_train 0.92 0.92 98.9 91.09 5.05e-45
seq_870_test seq_23219_train 1.00 0.99 92.0 91.08 1.61e-37
seq_594_test seq_8311_train 0.99 0.99 92.0 91.08 3.70e-38
seq_529_test seq_16431_train 0.99 0.99 92.0 91.08 3.70e-38
seq_658_test seq_13647_train 0.98 0.98 92.9 91.04 4.03e-39
seq_534_test seq_24690_train 0.98 0.98 92.9 91.04 4.03e-39
seq_990_test seq_17283_train 0.98 0.98 92.9 91.04 4.03e-39
seq_884_test seq_25266_train 0.98 0.98 92.9 91.04 4.03e-39
seq_884_test seq_15894_train 0.98 0.98 92.9 91.04 4.03e-39
seq_675_test seq_22029_train 0.96 0.96 94.8 91.01 4.56e-41
seq_643_test seq_25942_train 1.00 1.00 91.0 91.00 3.36e-37
seq_724_test seq_30495_train 1.00 1.00 91.0 91.00 3.36e-37
seq_884_test seq_2367_train 1.00 1.00 91.0 91.00 3.36e-37
seq_534_test seq_23590_train 0.97 0.97 93.8 90.99 4.32e-40
seq_534_test seq_11240_train 0.97 0.97 93.8 90.99 4.32e-40
seq_628_test seq_15119_train 0.97 0.97 93.8 90.99 4.32e-40
seq_865_test seq_23530_train 0.97 0.97 93.8 90.99 4.32e-40
seq_884_test seq_6987_train 0.97 0.97 93.8 90.99 4.32e-40
seq_684_test seq_6574_train 0.99 0.98 92.0 90.16 6.99e-37
seq_955_test seq_6725_train 0.99 0.98 92.0 90.16 6.99e-37
seq_955_test seq_21549_train 0.95 0.94 95.8 90.15 9.67e-41
seq_798_test seq_21531_train 0.96 0.98 93.9 90.14 3.70e-38
seq_841_test seq_5627_train 0.93 0.93 96.8 90.12 2.24e-42
seq_955_test seq_22654_train 0.98 0.97 92.9 90.11 7.74e-38
seq_675_test seq_24080_train 0.91 0.91 98.9 90.10 2.33e-44
seq_675_test seq_11507_train 0.99 1.00 91.0 90.09 6.22e-36
seq_594_test seq_3237_train 0.99 0.99 91.0 90.09 1.45e-36
seq_594_test seq_4766_train 0.99 0.99 91.0 90.09 1.45e-36
seq_529_test seq_28805_train 0.99 0.99 91.0 90.09 1.45e-36
seq_529_test seq_26255_train 0.99 0.99 91.0 90.09 1.45e-36
seq_990_test seq_7298_train 0.99 0.99 91.0 90.09 1.45e-36
seq_641_test seq_1076_train 0.99 0.99 91.0 90.09 1.45e-36
seq_955_test seq_7371_train 1.00 0.99 91.0 90.09 6.22e-36
seq_803_test seq_27508_train 0.99 0.99 91.0 90.09 1.45e-36
seq_537_test seq_5908_train 0.99 0.99 91.0 90.09 1.45e-36
seq_841_test seq_961_train 0.92 0.92 97.8 90.07 2.30e-43
seq_998_test seq_11617_train 0.98 0.98 91.9 90.06 1.61e-37
seq_675_test seq_28203_train 0.98 0.98 91.9 90.06 1.61e-37
seq_684_test seq_20376_train 0.98 0.98 91.9 90.06 1.61e-37
seq_534_test seq_16684_train 0.98 0.98 91.9 90.06 1.61e-37
seq_803_test seq_7123_train 0.98 0.98 91.9 90.06 1.61e-37
seq_870_test seq_599_train 0.96 0.95 94.8 90.06 9.10e-40
seq_529_test seq_1052_train 0.96 0.96 93.8 90.05 1.91e-39
seq_628_test seq_13224_train 0.96 0.96 93.8 90.05 1.91e-39
seq_658_test seq_8843_train 0.97 0.97 92.8 90.02 1.77e-38
seq_534_test seq_4992_train 0.97 0.97 92.8 90.02 1.77e-38
seq_628_test seq_3184_train 0.97 0.97 92.8 90.02 1.77e-38
seq_990_test seq_8906_train 0.97 0.97 92.8 90.02 1.77e-38
seq_990_test seq_13365_train 0.97 0.97 92.8 90.02 1.77e-38
seq_803_test seq_392_train 0.97 0.97 92.8 90.02 1.77e-38
seq_707_test seq_22855_train 1.00 1.00 90.0 90.00 1.28e-35
seq_594_test seq_22948_train 1.00 1.00 90.0 90.00 1.28e-35
seq_594_test seq_23293_train 1.00 1.00 90.0 90.00 1.28e-35
seq_534_test seq_7904_train 1.00 1.00 90.0 90.00 1.28e-35
seq_534_test seq_26505_train 1.00 1.00 90.0 90.00 1.28e-35
seq_534_test seq_12977_train 1.00 1.00 90.0 90.00 1.28e-35