leeHom: adaptor trimming and merging for Illumina sequencing reads
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The sequencing of libraries containing molecules shorter than the read length, such as in ancient or forensic applications, may result in the production of reads that include the adaptor, and in paired reads that overlap one another. Challenges for the processing of such reads are the accurate identification of the adaptor sequence and accurate reconstruction of the original sequence most likely to have given rise to the observed read(s). We introduce an algorithm that removes the adaptors and reconstructs the original DNA sequences using a Bayesian maximum a posteriori probability approach. Our algorithm is faster, and provides a more accurate reconstruction of the original sequence for both simulated and ancient DNA data sets, than other approaches. leeHom is released under the GPLv3 and is freely available from: https://bioinf.eva.mpg.de/leehom/
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it