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_test.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 22:46:25

Basic Descriptive Statistics

Filename mrl-sample-designed_test.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_test.csv.gz mrl-sample-designed_train.csv.gz
Data Leakage (percentage) 100.00% 99.66%
Data Leakage (count) 15003 69775
Similarity Histogram
4500900 high-similarity alignments (first 100 shown)
Query (Q) Target (T) Q Cov. T Cov. % Identity % Similarity E-value Alignment
seq_2952_test seq_24787_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2952_test seq_6588_train 1.00 1.00 99.8 99.80 0.00e+00
seq_3016_test seq_49472_train 1.00 1.00 99.8 99.80 0.00e+00
seq_3080_test seq_66496_train 1.00 1.00 99.8 99.80 0.00e+00
seq_3112_test seq_16274_train 1.00 1.00 99.8 99.80 0.00e+00
seq_3112_test seq_24247_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8446_test seq_50446_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8606_test seq_24972_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8606_test seq_47859_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8670_test seq_61080_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8734_test seq_34431_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12546_test seq_39176_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12578_test seq_45488_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12610_test seq_15468_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12610_test seq_11192_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12738_test seq_35745_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12738_test seq_4774_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7996_test seq_44307_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8028_test seq_59075_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8028_test seq_14684_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8092_test seq_6024_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8124_test seq_47260_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8156_test seq_33485_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8220_test seq_16056_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8220_test seq_3515_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8252_test seq_31245_train 1.00 1.00 99.8 99.80 0.00e+00
seq_788_test seq_68732_train 1.00 1.00 99.8 99.80 0.00e+00
seq_884_test seq_68934_train 1.00 1.00 99.8 99.80 0.00e+00
seq_916_test seq_52944_train 1.00 1.00 99.8 99.80 0.00e+00
seq_948_test seq_8232_train 1.00 1.00 99.8 99.80 0.00e+00
seq_297_test seq_69901_train 1.00 1.00 99.8 99.80 0.00e+00
seq_329_test seq_16326_train 1.00 1.00 99.8 99.80 0.00e+00
seq_393_test seq_62632_train 1.00 1.00 99.8 99.80 0.00e+00
seq_393_test seq_46604_train 1.00 1.00 99.8 99.80 0.00e+00
seq_425_test seq_7953_train 1.00 1.00 99.8 99.80 0.00e+00
seq_457_test seq_9574_train 1.00 1.00 99.8 99.80 0.00e+00
seq_521_test seq_19513_train 1.00 1.00 99.8 99.80 0.00e+00
seq_419_test seq_23382_train 1.00 1.00 99.8 99.80 0.00e+00
seq_451_test seq_24149_train 1.00 1.00 99.8 99.80 0.00e+00
seq_515_test seq_4733_train 1.00 1.00 99.8 99.80 0.00e+00
seq_547_test seq_12711_train 1.00 1.00 99.8 99.80 0.00e+00
seq_579_test seq_7824_train 1.00 1.00 99.8 99.80 0.00e+00
seq_611_test seq_31123_train 1.00 1.00 99.8 99.80 0.00e+00
seq_643_test seq_68436_train 1.00 1.00 99.8 99.80 0.00e+00
seq_675_test seq_52615_train 1.00 1.00 99.8 99.80 0.00e+00
seq_707_test seq_60473_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1808_test seq_56296_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1840_test seq_23386_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1872_test seq_66401_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1872_test seq_31416_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1904_test seq_13289_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1904_test seq_17841_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1936_test seq_10310_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2032_test seq_7680_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2032_test seq_43736_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2032_test seq_55899_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2064_test seq_35491_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14298_test seq_23746_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14330_test seq_48738_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14330_test seq_19722_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14362_test seq_1614_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14426_test seq_1001_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14426_test seq_31797_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14458_test seq_43152_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14522_test seq_51063_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14554_test seq_28404_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8272_test seq_44648_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8304_test seq_64692_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8336_test seq_52896_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8368_test seq_34823_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8368_test seq_36812_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8368_test seq_51281_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8400_test seq_298_train 1.00 1.00 99.8 99.80 0.00e+00
seq_3784_test seq_55429_train 1.00 1.00 99.8 99.80 0.00e+00
seq_3784_test seq_68816_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4040_test seq_63013_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10260_test seq_43121_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10324_test seq_21125_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10388_test seq_7649_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10420_test seq_39206_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10452_test seq_135_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10452_test seq_34239_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10548_test seq_36817_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10548_test seq_48569_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5572_test seq_33217_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5636_test seq_12610_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5636_test seq_37631_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5700_test seq_60136_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5700_test seq_2745_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5732_test seq_3055_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5764_test seq_62051_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5796_test seq_53907_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5828_test seq_64673_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5828_test seq_14279_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4754_test seq_22175_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4786_test seq_45217_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4786_test seq_36269_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4786_test seq_40562_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4850_test seq_40730_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6913_test seq_61889_train 1.00 1.00 99.8 99.80 0.00e+00