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 H3K9ac_test.csv.gz against train set H3K9ac_train.csv.gz
Data Leakage:!WarningHow a flag is decided →
gb-qc v1.0.0 · run 2026-09-15 22:31:20

Basic Descriptive Statistics

Filename H3K9ac_test.csv.gz H3K9ac_train.csv.gz
Number of sequences 1004 23274
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 H3K9ac_test.csv.gz H3K9ac_train.csv.gz
Data Leakage (percentage) 1.00% 0.07%
Data Leakage (count) 10 16
Similarity Histogram
16 high-similarity alignments
Query (Q) Target (T) Q Cov. T Cov. % Identity % Similarity E-value Alignment
seq_910_test seq_12285_train 0.99 0.99 96.9 96.22 0.00e+00
seq_714_test seq_17226_train 0.98 0.98 97.1 95.26 0.00e+00
seq_910_test seq_12428_train 0.99 0.99 96.0 94.94 0.00e+00
seq_524_test seq_18694_train 0.96 0.96 97.6 94.09 0.00e+00
seq_812_test seq_13697_train 0.99 1.00 94.6 94.03 0.00e+00
seq_869_test seq_16567_train 0.96 0.96 97.3 93.51 0.00e+00
seq_995_test seq_12567_train 0.99 0.98 94.8 93.28 0.00e+00
seq_869_test seq_22047_train 0.95 0.95 98.4 93.18 0.00e+00
seq_688_test seq_13675_train 0.99 0.99 94.1 92.88 0.00e+00
seq_665_test seq_13430_train 0.99 1.00 93.1 92.63 0.00e+00
seq_869_test seq_17603_train 0.95 0.95 97.1 92.05 0.00e+00
seq_773_test seq_20129_train 0.96 0.96 95.6 91.39 0.00e+00
seq_688_test seq_17087_train 0.93 0.93 97.3 90.88 0.00e+00
seq_665_test seq_20162_train 0.99 1.00 91.4 90.58 0.00e+00
seq_988_test seq_16229_train 0.95 0.95 95.6 90.53 0.00e+00
seq_665_test seq_20503_train 0.96 0.96 93.6 90.23 0.00e+00