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-m1pseudo_val.csv.gz against train set mrl-sample-egfp-m1pseudo_train.csv.gz
Data Leakage:✖FailHow a flag is decided →
gb-qc v1.0.0 · run 2026-09-16 01:59:29

Basic Descriptive Statistics

Filename mrl-sample-egfp-m1pseudo_val.csv.gz mrl-sample-egfp-m1pseudo_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-m1pseudo_val.csv.gz mrl-sample-egfp-m1pseudo_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_42394_test seq_53693_train 1.00 1.00 99.8 99.80 0.00e+00
seq_46435_test seq_97407_train 1.00 1.00 99.8 99.80 0.00e+00
seq_46563_test seq_54485_train 1.00 1.00 99.8 99.80 0.00e+00
seq_20169_test seq_18918_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_25231_test seq_125284_train 1.00 1.00 99.8 99.80 0.00e+00
seq_11608_test seq_35134_train 1.00 1.00 99.8 99.80 0.00e+00
seq_26468_test seq_13479_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1831_test seq_77720_train 1.00 1.00 99.8 99.80 0.00e+00
seq_34182_test seq_40381_train 1.00 1.00 99.8 99.80 0.00e+00
seq_40550_test seq_84460_train 1.00 1.00 99.8 99.80 0.00e+00
seq_37370_test seq_222256_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14100_test seq_61083_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_39973_test seq_104573_train 1.00 1.00 99.8 99.80 0.00e+00
seq_40069_test seq_162514_train 1.00 1.00 99.8 99.80 0.00e+00
seq_15061_test seq_169488_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7806_test seq_208559_train 1.00 1.00 99.8 99.80 0.00e+00
seq_16685_test seq_177274_train 1.00 1.00 99.8 99.80 0.00e+00
seq_30289_test seq_1076_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_22361_test seq_43283_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9942_test seq_116403_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10418_test seq_133153_train 1.00 1.00 99.8 99.80 0.00e+00
seq_44956_test seq_18054_train 1.00 1.00 99.8 99.80 0.00e+00
seq_34845_test seq_220017_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13219_test seq_105602_train 1.00 1.00 99.8 99.80 0.00e+00
seq_29801_test seq_92749_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4021_test seq_25405_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14274_test seq_153816_train 1.00 1.00 99.8 99.80 0.00e+00
seq_25559_test seq_43908_train 1.00 1.00 99.8 99.80 0.00e+00
seq_140_test seq_198745_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1867_test seq_81907_train 1.00 1.00 99.8 99.80 0.00e+00
seq_29231_test seq_13251_train 1.00 1.00 99.8 99.80 0.00e+00
seq_18367_test seq_63388_train 1.00 1.00 99.8 99.80 0.00e+00
seq_3271_test seq_151028_train 1.00 1.00 99.8 99.80 0.00e+00
seq_44238_test seq_16366_train 1.00 1.00 99.8 99.80 0.00e+00
seq_44270_test seq_141834_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7212_test seq_204948_train 1.00 1.00 99.8 99.80 0.00e+00
seq_39667_test seq_108479_train 1.00 1.00 99.8 99.80 0.00e+00
seq_43030_test seq_70515_train 1.00 1.00 99.8 99.80 0.00e+00
seq_11198_test seq_155621_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_13384_test seq_8694_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_33593_test seq_105478_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14663_test seq_214413_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_12177_test seq_22199_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4449_test seq_190074_train 1.00 1.00 99.8 99.80 0.00e+00
seq_26341_test seq_167958_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_2552_test seq_175736_train 1.00 1.00 99.8 99.80 0.00e+00
seq_28418_test seq_169689_train 1.00 1.00 99.8 99.80 0.00e+00
seq_17168_test seq_145994_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14220_test seq_140106_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12321_test seq_215826_train 1.00 1.00 99.8 99.80 0.00e+00
seq_42119_test seq_6534_train 1.00 1.00 99.8 99.80 0.00e+00
seq_15008_test seq_179721_train 1.00 1.00 99.8 99.80 0.00e+00
seq_47013_test seq_216320_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5702_test seq_92801_train 1.00 1.00 99.8 99.80 0.00e+00
seq_30391_test seq_68234_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8923_test seq_97192_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13181_test seq_140735_train 1.00 1.00 99.8 99.80 0.00e+00
seq_35876_test seq_81143_train 1.00 1.00 99.8 99.80 0.00e+00
seq_36036_test seq_138181_train 1.00 1.00 99.8 99.80 0.00e+00
seq_521_test seq_130260_train 1.00 1.00 99.8 99.80 0.00e+00
seq_38849_test seq_11637_train 1.00 1.00 99.8 99.80 0.00e+00
seq_38267_test seq_80432_train 1.00 1.00 99.8 99.80 0.00e+00
seq_20862_test seq_3425_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4216_test seq_162153_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4280_test seq_150415_train 1.00 1.00 99.8 99.80 0.00e+00
seq_773_test seq_121621_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_43829_test seq_136519_train 1.00 1.00 99.8 99.80 0.00e+00
seq_41966_test seq_34031_train 1.00 1.00 99.8 99.80 0.00e+00
seq_33368_test seq_111608_train 1.00 1.00 99.8 99.80 0.00e+00
seq_32482_test seq_123449_train 1.00 1.00 99.8 99.80 0.00e+00
seq_37989_test seq_44038_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_31342_test seq_122192_train 1.00 1.00 99.8 99.80 0.00e+00
seq_40048_test seq_90735_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14819_test seq_38540_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14979_test seq_219175_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_32886_test seq_112941_train 1.00 1.00 99.8 99.80 0.00e+00
seq_3393_test seq_160562_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_18179_test seq_65198_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8712_test seq_209051_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_6122_test seq_53996_train 1.00 1.00 99.8 99.80 0.00e+00
seq_28457_test seq_49178_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_28105_test seq_186794_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_35631_test seq_158111_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8029_test seq_164886_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13604_test seq_122174_train 1.00 1.00 99.8 99.80 0.00e+00