Summary

Basic Descriptive Statistics
! Data Leakage
Documentation GitHub
Find the shortcut. Learn the biology.
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 H3K4me2_test.csv.gz against train set H3K4me2_train.csv.gz
Data Leakage:!WarningHow a flag is decided →
gb-qc v1.0.0 · run 2026-09-15 22:31:16

Basic Descriptive Statistics

Filename H3K4me2_test.csv.gz H3K4me2_train.csv.gz
Number of sequences 2138 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 H3K4me2_test.csv.gz H3K4me2_train.csv.gz
Data Leakage (percentage) 0.89% 0.11%
Data Leakage (count) 19 33
Similarity Histogram
45 high-similarity alignments
Query (Q) Target (T) Q Cov. T Cov. % Identity % Similarity E-value Alignment
seq_1562_test seq_26015_train 1.00 1.00 97.0 96.71 0.00e+00
seq_1269_test seq_21536_train 1.00 1.00 96.4 96.21 0.00e+00
seq_1595_test seq_16250_train 0.99 0.99 96.1 95.62 0.00e+00
seq_1438_test seq_16250_train 0.99 0.99 96.1 95.62 0.00e+00
seq_1202_test seq_19513_train 0.99 1.00 95.5 94.83 0.00e+00
seq_1819_test seq_15867_train 0.98 0.98 96.8 94.57 0.00e+00
seq_1595_test seq_24384_train 0.99 0.99 95.0 94.43 0.00e+00
seq_1438_test seq_24384_train 0.99 0.99 95.0 94.43 0.00e+00
seq_1957_test seq_6816_train 0.99 0.99 95.5 94.16 0.00e+00
seq_1251_test seq_252_train 0.97 0.97 97.1 93.99 0.00e+00
seq_1627_test seq_24763_train 0.97 0.97 96.8 93.70 0.00e+00
seq_1149_test seq_15273_train 0.97 0.97 96.5 93.61 0.00e+00
seq_1957_test seq_21832_train 0.98 0.98 95.0 93.29 0.00e+00
seq_1562_test seq_22676_train 0.96 0.96 96.7 93.12 0.00e+00
seq_2033_test seq_24182_train 0.96 0.96 97.3 93.12 0.00e+00
seq_1957_test seq_11747_train 0.98 0.98 95.1 93.10 0.00e+00
seq_1595_test seq_11911_train 0.99 0.99 93.3 92.55 0.00e+00
seq_1438_test seq_11911_train 0.99 0.99 93.3 92.55 0.00e+00
seq_2101_test seq_15273_train 0.95 0.96 96.8 92.44 0.00e+00
seq_1956_test seq_15273_train 0.95 0.96 96.8 92.44 0.00e+00
seq_2033_test seq_27684_train 0.97 0.97 94.9 92.34 0.00e+00
seq_1200_test seq_4848_train 0.98 0.98 94.3 92.23 0.00e+00
seq_1957_test seq_14776_train 0.96 0.96 95.7 92.06 0.00e+00
seq_1562_test seq_22114_train 0.96 0.96 96.1 91.97 0.00e+00
seq_1202_test seq_15867_train 0.95 0.95 97.0 91.96 0.00e+00
seq_1987_test seq_26131_train 0.98 0.98 94.0 91.93 0.00e+00
seq_2052_test seq_25951_train 0.98 0.99 93.5 91.91 0.00e+00
seq_1819_test seq_19513_train 0.97 0.97 95.0 91.86 0.00e+00
seq_2101_test seq_206_train 0.95 0.96 96.0 91.68 0.00e+00
seq_1956_test seq_206_train 0.95 0.96 96.0 91.68 0.00e+00
seq_1595_test seq_12545_train 0.97 0.97 94.5 91.57 0.00e+00
seq_1438_test seq_12545_train 0.97 0.97 94.5 91.57 0.00e+00
seq_1957_test seq_7883_train 0.95 0.96 95.9 91.49 0.00e+00
seq_1562_test seq_7214_train 0.95 0.96 95.7 91.39 0.00e+00
seq_1987_test seq_4218_train 0.97 0.97 93.8 91.27 0.00e+00
seq_1202_test seq_3485_train 0.94 0.94 96.8 91.19 0.00e+00
seq_1627_test seq_65_train 0.94 0.94 96.9 90.99 0.00e+00
seq_1745_test seq_206_train 0.98 0.98 93.0 90.95 0.00e+00
seq_1422_test seq_10206_train 1.00 1.00 91.3 90.93 0.00e+00
seq_1177_test seq_17535_train 0.96 0.96 94.3 90.81 0.00e+00
seq_1819_test seq_3485_train 0.94 0.94 96.3 90.71 0.00e+00
seq_1149_test seq_206_train 0.94 0.94 96.6 90.61 0.00e+00
seq_1202_test seq_13598_train 0.93 0.93 97.1 90.59 0.00e+00
seq_1562_test seq_8644_train 0.93 0.93 97.1 90.40 0.00e+00
seq_1627_test seq_3693_train 0.93 0.93 96.6 90.13 0.00e+00