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 mrl-sample-designed_val.csv.gz against train set mrl-sample-designed_train.csv.gz
Data Leakage:✖FailHow a flag is decided →
gb-qc v1.0.0 · run 2026-09-15 22:53:48

Basic Descriptive Statistics

Filename mrl-sample-designed_val.csv.gz mrl-sample-designed_train.csv.gz
Number of sequences 15003 70011
Minimum length 855 855
Mean length 855.00 855.00
Maximum length 855 855
✖

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 mrl-sample-designed_val.csv.gz mrl-sample-designed_train.csv.gz
Data Leakage (percentage) 100.00% 99.69%
Data Leakage (count) 15003 69793
Similarity Histogram
4500900 high-similarity alignments (first 100 shown)
Query (Q) Target (T) Q Cov. T Cov. % Identity % Similarity E-value Alignment
seq_6938_test seq_59715_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7066_test seq_56584_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7098_test seq_13479_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7162_test seq_43664_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7162_test seq_68880_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7194_test seq_17067_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12655_test seq_55129_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12879_test seq_55442_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12911_test seq_64554_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12911_test seq_2189_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12943_test seq_61410_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12943_test seq_8942_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12071_test seq_60704_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12071_test seq_26079_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12327_test seq_65357_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12359_test seq_21784_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7263_test seq_37520_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7423_test seq_6998_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7519_test seq_17130_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1046_test seq_16040_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1078_test seq_8652_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1174_test seq_62718_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1174_test seq_36095_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1206_test seq_43846_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1238_test seq_66011_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8947_test seq_23614_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8979_test seq_12609_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9043_test seq_37660_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9139_test seq_20285_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9235_test seq_41509_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6443_test seq_33893_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6507_test seq_56266_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6507_test seq_12149_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6635_test seq_25023_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6667_test seq_53846_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6699_test seq_31037_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8000_test seq_50979_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8064_test seq_69491_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8096_test seq_20356_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8096_test seq_21577_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8096_test seq_43182_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8096_test seq_47088_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8096_test seq_7959_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8096_test seq_23802_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8096_test seq_57051_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8096_test seq_66207_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8128_test seq_50087_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8128_test seq_49143_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8160_test seq_38951_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8224_test seq_37730_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8224_test seq_57506_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8224_test seq_15437_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8224_test seq_46801_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8224_test seq_36726_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8224_test seq_36633_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8288_test seq_48749_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9079_test seq_35365_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_23462_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_15431_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_17160_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_12105_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_19402_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_48464_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_39282_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_49685_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_38294_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_11577_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_19705_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_29211_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_15356_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_24604_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_46268_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9207_test seq_5149_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2191_test seq_21676_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2223_test seq_28322_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2223_test seq_49425_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2287_test seq_46541_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2383_test seq_33409_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1191_test seq_32155_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1255_test seq_58898_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1287_test seq_8187_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1351_test seq_4037_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1415_test seq_27143_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5536_test seq_36528_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5632_test seq_6151_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5632_test seq_15986_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5664_test seq_69986_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5696_test seq_55976_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5728_test seq_65775_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1805_test seq_49812_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1869_test seq_33983_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1933_test seq_39345_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1997_test seq_24387_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5592_test seq_2707_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5624_test seq_40116_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5656_test seq_30560_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5688_test seq_32519_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10044_test seq_38618_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10108_test seq_60928_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10108_test seq_6716_train 1.00 1.00 99.8 99.80 0.00e+00