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 H3K4me1_test.csv.gz against train set H3K4me1_train.csv.gz
Data Leakage:!WarningHow a flag is decided →
gb-qc v1.0.0 · run 2026-09-15 22:31:14

Basic Descriptive Statistics

Filename H3K4me1_test.csv.gz H3K4me1_train.csv.gz
Number of sequences 3000 30000
Minimum length 1000 1000
Mean length 1000.00 1000.00
Maximum length 1000 1000
!

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 H3K4me1_test.csv.gz H3K4me1_train.csv.gz
Data Leakage (percentage) 0.87% 0.18%
Data Leakage (count) 26 53
Similarity Histogram
62 high-similarity alignments
Query (Q) Target (T) Q Cov. T Cov. % Identity % Similarity E-value Alignment
seq_2098_test seq_21891_train 1.00 1.00 97.4 97.01 0.00e+00
seq_1541_test seq_1792_train 1.00 1.00 96.7 96.31 0.00e+00
seq_2482_test seq_28059_train 1.00 1.00 96.3 96.11 0.00e+00
seq_148_test seq_9081_train 1.00 1.00 96.1 95.81 0.00e+00
seq_610_test seq_206_train 0.99 0.99 96.8 95.64 0.00e+00
seq_1131_test seq_206_train 0.99 0.99 96.3 95.63 0.00e+00
seq_352_test seq_3474_train 1.00 0.99 95.9 95.32 0.00e+00
seq_1641_test seq_21785_train 0.98 0.98 97.0 95.06 0.00e+00
seq_1931_test seq_6449_train 0.99 0.99 95.9 95.04 0.00e+00
seq_2482_test seq_5136_train 0.99 0.98 96.5 94.96 0.00e+00
seq_202_test seq_27690_train 0.99 1.00 95.4 94.83 0.00e+00
seq_2132_test seq_12624_train 0.97 0.97 97.6 94.77 0.00e+00
seq_352_test seq_28227_train 0.99 0.98 96.1 94.56 0.00e+00
seq_1541_test seq_25438_train 0.99 0.99 95.3 94.25 0.00e+00
seq_148_test seq_23713_train 1.00 1.00 94.2 94.11 0.00e+00
seq_2098_test seq_17678_train 0.96 0.96 97.9 94.08 0.00e+00
seq_450_test seq_9335_train 0.98 0.98 95.6 93.88 0.00e+00
seq_352_test seq_9830_train 0.99 0.99 94.7 93.75 0.00e+00
seq_70_test seq_20590_train 0.96 0.97 97.1 93.70 0.00e+00
seq_352_test seq_539_train 0.98 0.97 96.0 93.60 0.00e+00
seq_1541_test seq_27690_train 0.98 0.98 95.5 93.49 0.00e+00
seq_450_test seq_22643_train 0.97 0.97 96.1 93.22 0.00e+00
seq_1931_test seq_4226_train 0.98 0.98 95.3 93.20 0.00e+00
seq_936_test seq_15253_train 0.98 0.98 95.1 93.20 0.00e+00
seq_2098_test seq_4399_train 0.95 0.95 98.1 93.10 0.00e+00
seq_1390_test seq_9746_train 1.00 0.99 93.2 92.73 0.00e+00
seq_1414_test seq_10482_train 0.95 0.95 97.2 92.73 0.00e+00
seq_1414_test seq_21090_train 0.97 0.96 95.9 92.45 0.00e+00
seq_202_test seq_25302_train 0.98 0.99 94.2 92.41 0.00e+00
seq_1138_test seq_21347_train 0.97 0.96 95.7 92.35 0.00e+00
seq_2482_test seq_19526_train 0.96 0.96 96.2 92.16 0.00e+00
seq_128_test seq_29291_train 0.97 0.97 95.4 92.16 0.00e+00
seq_1390_test seq_20485_train 1.00 1.00 92.3 92.12 0.00e+00
seq_1541_test seq_9867_train 0.96 0.96 95.8 92.06 0.00e+00
seq_1541_test seq_25302_train 0.96 0.96 96.0 91.97 0.00e+00
seq_202_test seq_25438_train 0.98 0.99 93.6 91.92 0.00e+00
seq_128_test seq_12047_train 0.97 0.97 95.1 91.87 0.00e+00
seq_2245_test seq_5136_train 0.95 0.95 96.7 91.77 0.00e+00
seq_470_test seq_16570_train 0.97 0.97 94.5 91.76 0.00e+00
seq_202_test seq_1792_train 0.97 0.98 94.5 91.76 0.00e+00
seq_352_test seq_22118_train 1.00 0.99 92.7 91.68 0.00e+00
seq_2712_test seq_20590_train 0.94 0.94 97.3 91.66 0.00e+00
seq_1138_test seq_9416_train 0.98 0.98 93.4 91.63 0.00e+00
seq_1931_test seq_27988_train 0.96 0.96 95.6 91.58 0.00e+00
seq_128_test seq_3514_train 0.95 0.95 96.2 91.49 0.00e+00
seq_936_test seq_10482_train 0.94 0.94 96.7 91.19 0.00e+00
seq_1390_test seq_1282_train 0.99 0.99 91.8 91.16 0.00e+00
seq_1208_test seq_10903_train 0.98 0.98 93.1 91.05 0.00e+00
seq_1651_test seq_10320_train 0.98 0.98 92.9 91.04 0.00e+00
seq_165_test seq_16336_train 0.92 0.92 98.4 90.92 0.00e+00
seq_128_test seq_1_train 0.97 0.96 94.4 90.91 0.00e+00
seq_1899_test seq_24393_train 1.00 0.99 92.0 90.90 0.00e+00
seq_128_test seq_12476_train 0.96 0.96 94.7 90.72 0.00e+00
seq_1931_test seq_20391_train 0.97 0.97 93.7 90.70 0.00e+00
seq_1390_test seq_23546_train 0.99 0.99 91.7 90.69 0.00e+00
seq_1931_test seq_24138_train 1.00 0.99 91.2 90.65 0.00e+00
seq_352_test seq_16355_train 0.98 0.97 93.2 90.59 0.00e+00
seq_1931_test seq_23773_train 0.95 0.95 95.2 90.15 0.00e+00
seq_2245_test seq_28059_train 0.94 0.94 96.3 90.14 0.00e+00
seq_470_test seq_24762_train 0.99 0.99 91.1 90.10 0.00e+00
seq_128_test seq_24375_train 0.94 0.95 95.4 90.06 0.00e+00
seq_176_test seq_7016_train 0.94 0.94 95.9 90.05 0.00e+00