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-egfp-unmod_val.csv.gz against train set mrl-sample-egfp-unmod_train.csv.gz
Data Leakage:✖FailHow a flag is decided →
gb-qc v1.0.0 · run 2026-09-16 01:51:05

Basic Descriptive Statistics

Filename mrl-sample-egfp-unmod_val.csv.gz mrl-sample-egfp-unmod_train.csv.gz
Number of sequences 47770 222927
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-egfp-unmod_val.csv.gz mrl-sample-egfp-unmod_train.csv.gz
Data Leakage (percentage) 100.00% 99.90%
Data Leakage (count) 47770 222711
Similarity Histogram
14331000 high-similarity alignments (first 100 shown)
Query (Q) Target (T) Q Cov. T Cov. % Identity % Similarity E-value Alignment
seq_15014_test seq_122614_train 1.00 1.00 99.8 99.80 0.00e+00
seq_20836_test seq_187896_train 1.00 1.00 99.8 99.80 0.00e+00
seq_19755_test seq_72873_train 1.00 1.00 99.8 99.80 0.00e+00
seq_19947_test seq_13491_train 1.00 1.00 99.8 99.80 0.00e+00
seq_40396_test seq_166665_train 1.00 1.00 99.8 99.80 0.00e+00
seq_30669_test seq_79827_train 1.00 1.00 99.8 99.80 0.00e+00
seq_47642_test seq_93302_train 1.00 1.00 99.8 99.80 0.00e+00
seq_45508_test seq_86686_train 1.00 1.00 99.8 99.80 0.00e+00
seq_45636_test seq_196416_train 1.00 1.00 99.8 99.80 0.00e+00
seq_16585_test seq_158372_train 1.00 1.00 99.8 99.80 0.00e+00
seq_37009_test seq_109334_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9405_test seq_12597_train 1.00 1.00 99.8 99.80 0.00e+00
seq_26480_test seq_26199_train 1.00 1.00 99.8 99.80 0.00e+00
seq_35470_test seq_131844_train 1.00 1.00 99.8 99.80 0.00e+00
seq_32313_test seq_11116_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4010_test seq_96441_train 1.00 1.00 99.8 99.80 0.00e+00
seq_34143_test seq_218141_train 1.00 1.00 99.8 99.80 0.00e+00
seq_41253_test seq_18415_train 1.00 1.00 99.8 99.80 0.00e+00
seq_18935_test seq_201571_train 1.00 1.00 99.8 99.80 0.00e+00
seq_19127_test seq_80152_train 1.00 1.00 99.8 99.80 0.00e+00
seq_20500_test seq_142294_train 1.00 1.00 99.8 99.80 0.00e+00
seq_47531_test seq_220181_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12604_test seq_188659_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12700_test seq_27315_train 1.00 1.00 99.8 99.80 0.00e+00
seq_37093_test seq_59809_train 1.00 1.00 99.8 99.80 0.00e+00
seq_29104_test seq_127225_train 1.00 1.00 99.8 99.80 0.00e+00
seq_18508_test seq_183025_train 1.00 1.00 99.8 99.80 0.00e+00
seq_11391_test seq_126748_train 1.00 1.00 99.8 99.80 0.00e+00
seq_45218_test seq_61318_train 1.00 1.00 99.8 99.80 0.00e+00
seq_11729_test seq_44127_train 1.00 1.00 99.8 99.80 0.00e+00
seq_19927_test seq_83050_train 1.00 1.00 99.8 99.80 0.00e+00
seq_17220_test seq_195388_train 1.00 1.00 99.8 99.80 0.00e+00
seq_34114_test seq_4126_train 1.00 1.00 99.8 99.80 0.00e+00
seq_25742_test seq_171485_train 1.00 1.00 99.8 99.80 0.00e+00
seq_43624_test seq_210989_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13215_test seq_111527_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4576_test seq_162816_train 1.00 1.00 99.8 99.80 0.00e+00
seq_36527_test seq_25688_train 1.00 1.00 99.8 99.80 0.00e+00
seq_17424_test seq_146825_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13747_test seq_118960_train 1.00 1.00 99.8 99.80 0.00e+00
seq_27992_test seq_143645_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5773_test seq_3009_train 1.00 1.00 99.8 99.80 0.00e+00
seq_20482_test seq_73317_train 1.00 1.00 99.8 99.80 0.00e+00
seq_23496_test seq_198539_train 1.00 1.00 99.8 99.80 0.00e+00
seq_31588_test seq_174584_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4048_test seq_125879_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10096_test seq_19171_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10023_test seq_133795_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10151_test seq_16597_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10763_test seq_130945_train 1.00 1.00 99.8 99.80 0.00e+00
seq_21764_test seq_26312_train 1.00 1.00 99.8 99.80 0.00e+00
seq_30639_test seq_7719_train 1.00 1.00 99.8 99.80 0.00e+00
seq_22131_test seq_204017_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8141_test seq_19484_train 1.00 1.00 99.8 99.80 0.00e+00
seq_34488_test seq_111997_train 1.00 1.00 99.8 99.80 0.00e+00
seq_17951_test seq_5662_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13477_test seq_43975_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5886_test seq_22276_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4167_test seq_87192_train 1.00 1.00 99.8 99.80 0.00e+00
seq_18749_test seq_77587_train 1.00 1.00 99.8 99.80 0.00e+00
seq_15033_test seq_149058_train 1.00 1.00 99.8 99.80 0.00e+00
seq_29919_test seq_156157_train 1.00 1.00 99.8 99.80 0.00e+00
seq_17684_test seq_92343_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1403_test seq_150708_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1435_test seq_164355_train 1.00 1.00 99.8 99.80 0.00e+00
seq_36670_test seq_30166_train 1.00 1.00 99.8 99.80 0.00e+00
seq_36798_test seq_84540_train 1.00 1.00 99.8 99.80 0.00e+00
seq_210_test seq_124100_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7450_test seq_138650_train 1.00 1.00 99.8 99.80 0.00e+00
seq_42746_test seq_200587_train 1.00 1.00 99.8 99.80 0.00e+00
seq_26696_test seq_201222_train 1.00 1.00 99.8 99.80 0.00e+00
seq_33111_test seq_109168_train 1.00 1.00 99.8 99.80 0.00e+00
seq_46239_test seq_15882_train 1.00 1.00 99.8 99.80 0.00e+00
seq_31342_test seq_122192_train 1.00 1.00 99.8 99.80 0.00e+00
seq_33715_test seq_130129_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6206_test seq_52072_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4002_test seq_16529_train 1.00 1.00 99.8 99.80 0.00e+00
seq_25112_test seq_54715_train 1.00 1.00 99.8 99.80 0.00e+00
seq_32944_test seq_140408_train 1.00 1.00 99.8 99.80 0.00e+00
seq_44436_test seq_193325_train 1.00 1.00 99.8 99.80 0.00e+00
seq_44468_test seq_84271_train 1.00 1.00 99.8 99.80 0.00e+00
seq_11638_test seq_101390_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14903_test seq_189081_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14373_test seq_196894_train 1.00 1.00 99.8 99.80 0.00e+00
seq_21320_test seq_45702_train 1.00 1.00 99.8 99.80 0.00e+00
seq_40875_test seq_80192_train 1.00 1.00 99.8 99.80 0.00e+00
seq_45550_test seq_66355_train 1.00 1.00 99.8 99.80 0.00e+00
seq_15409_test seq_134093_train 1.00 1.00 99.8 99.80 0.00e+00
seq_470_test seq_148070_train 1.00 1.00 99.8 99.80 0.00e+00
seq_33043_test seq_189221_train 1.00 1.00 99.8 99.80 0.00e+00
seq_28063_test seq_147185_train 1.00 1.00 99.8 99.80 0.00e+00
seq_25053_test seq_199895_train 1.00 1.00 99.8 99.80 0.00e+00
seq_40259_test seq_51676_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10220_test seq_24275_train 1.00 1.00 99.8 99.80 0.00e+00
seq_15153_test seq_210282_train 1.00 1.00 99.8 99.80 0.00e+00
seq_20603_test seq_117074_train 1.00 1.00 99.8 99.80 0.00e+00
seq_20667_test seq_131451_train 1.00 1.00 99.8 99.80 0.00e+00
seq_39157_test seq_4030_train 1.00 1.00 99.8 99.80 0.00e+00
seq_37856_test seq_129985_train 1.00 1.00 99.8 99.80 0.00e+00
seq_39457_test seq_104141_train 1.00 1.00 99.8 99.80 0.00e+00