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-varying_val.csv.gz against train set mrl-sample-varying_train.csv.gz
Data Leakage:✖FailHow a flag is decided →
gb-qc v1.0.0 · run 2026-09-15 22:41:00

Basic Descriptive Statistics

Filename mrl-sample-varying_val.csv.gz mrl-sample-varying_train.csv.gz
Number of sequences 15979 74571
Minimum length 830 830
Mean length 866.82 866.91
Maximum length 905 905
✖

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-varying_val.csv.gz mrl-sample-varying_train.csv.gz
Data Leakage (percentage) 82.23% 72.02%
Data Leakage (count) 13139 53704
Similarity Histogram
1813689 high-similarity alignments (first 100 shown)
Query (Q) Target (T) Q Cov. T Cov. % Identity % Similarity E-value Alignment
seq_7833_test seq_14847_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8661_test seq_46224_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7945_test seq_2255_train 1.00 1.00 99.8 99.80 0.00e+00
seq_11913_test seq_4144_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13000_test seq_29590_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13000_test seq_55803_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14836_test seq_27217_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9430_test seq_27193_train 1.00 1.00 99.8 99.80 0.00e+00
seq_16_test seq_29378_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12724_test seq_57677_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6542_test seq_63177_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7394_test seq_67252_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5424_test seq_61314_train 1.00 1.00 99.8 99.80 0.00e+00
seq_3673_test seq_6074_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13163_test seq_16438_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13555_test seq_34199_train 1.00 1.00 99.8 99.80 0.00e+00
seq_11742_test seq_71044_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7676_test seq_72743_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12363_test seq_36864_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10665_test seq_11352_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8524_test seq_46762_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4676_test seq_67693_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10005_test seq_39862_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13171_test seq_71669_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5739_test seq_57257_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5879_test seq_70374_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6135_test seq_52469_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12394_test seq_21649_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7191_test seq_15824_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9428_test seq_7225_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6469_test seq_53412_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14585_test seq_37690_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8481_test seq_63594_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12517_test seq_65151_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6904_test seq_49269_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5578_test seq_46808_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14065_test seq_38993_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12615_test seq_62436_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13970_test seq_50778_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7462_test seq_60779_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14663_test seq_42872_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8264_test seq_7510_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8344_test seq_22473_train 1.00 1.00 99.8 99.80 0.00e+00
seq_15552_test seq_9709_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6341_test seq_66544_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9910_test seq_33809_train 1.00 1.00 99.8 99.80 0.00e+00
seq_15237_test seq_29747_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6205_test seq_12418_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4880_test seq_37598_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5119_test seq_30784_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5119_test seq_72260_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9434_test seq_30400_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12831_test seq_46207_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5649_test seq_69529_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2614_test seq_50239_train 1.00 1.00 99.8 99.80 0.00e+00
seq_453_test seq_52149_train 1.00 1.00 99.8 99.80 0.00e+00
seq_549_test seq_23799_train 1.00 1.00 99.8 99.80 0.00e+00
seq_11428_test seq_54945_train 1.00 1.00 99.8 99.80 0.00e+00
seq_11004_test seq_27210_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14089_test seq_74553_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14782_test seq_69279_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10149_test seq_31096_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10213_test seq_71815_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4701_test seq_60045_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8045_test seq_62171_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1322_test seq_6251_train 1.00 1.00 99.8 99.80 0.00e+00
seq_6620_test seq_60758_train 1.00 1.00 99.8 99.80 0.00e+00
seq_8074_test seq_27566_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9445_test seq_66707_train 1.00 1.00 99.8 99.80 0.00e+00
seq_12967_test seq_18140_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1526_test seq_62227_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13102_test seq_37642_train 1.00 1.00 99.8 99.80 0.00e+00
seq_1648_test seq_19380_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2535_test seq_22172_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2946_test seq_57480_train 1.00 1.00 99.8 99.80 0.00e+00
seq_3414_test seq_44948_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13157_test seq_3589_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13157_test seq_62361_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4070_test seq_25322_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2958_test seq_30019_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2889_test seq_8140_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2889_test seq_43884_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14463_test seq_32291_train 1.00 1.00 99.8 99.80 0.00e+00
seq_13899_test seq_10371_train 1.00 1.00 99.8 99.80 0.00e+00
seq_619_test seq_8069_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2457_test seq_53527_train 1.00 1.00 99.8 99.80 0.00e+00
seq_7732_test seq_50426_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2674_test seq_70295_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5677_test seq_14419_train 1.00 1.00 99.8 99.80 0.00e+00
seq_10916_test seq_65656_train 1.00 1.00 99.8 99.80 0.00e+00
seq_15835_test seq_59692_train 1.00 1.00 99.8 99.80 0.00e+00
seq_951_test seq_3097_train 1.00 1.00 99.8 99.80 0.00e+00
seq_11480_test seq_22090_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4521_test seq_22534_train 1.00 1.00 99.8 99.80 0.00e+00
seq_2523_test seq_70082_train 1.00 1.00 99.8 99.80 0.00e+00
seq_9471_test seq_55380_train 1.00 1.00 99.8 99.80 0.00e+00
seq_5095_test seq_58921_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14967_test seq_62737_train 1.00 1.00 99.8 99.80 0.00e+00
seq_14538_test seq_31868_train 1.00 1.00 99.8 99.80 0.00e+00
seq_4743_test seq_62056_train 1.00 1.00 99.8 99.80 0.00e+00