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Record W6958598138 · doi:10.6084/m9.figshare.16909621

Additional file 1 of LongStitch: high-quality genome assembly correction and scaffolding using long reads

2021· article· en· W6958598138 on OpenAlexaff

Bibliographic record

VenueFigshare · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsCanada's Michael Smith Genome Sciences Centre
Fundersnot available
KeywordsCorrectnessBenchmarkingTable (database)Contiguity

Abstract

fetched live from OpenAlex

Additional file 1. Table S1. Sequencing data used for the correction and scaffolding runs. Table S2. Baseline assemblies used for correction and scaffolding runs. Table S3. Availability of baseline assemblies used for correction and scaffolding runs. Table S4. Reference genome builds used for QUAST assembly analysis. Table S5. Contiguity, correctness and benchmarking statistics for running the default steps of LongStitch (up to ntLink) on human assemblies. Table S6. Contiguity, correctness and benchmarking statistics for running LRScaf on human assemblies. Table S7. Contiguity, correctness and benchmarking statistics for running OPERA-LG on human assemblies. Table S8. Contiguity, correctness and benchmarking statistics for running LongStitch, LRScaf and OPERA-LG on C. elegans assemblies. Table S9. Contiguity, correctness and benchmarking statistics for running LongStitch, LRScaf and OPERA-LG on O. sativa assemblies. Table S10. Positive predictive value (PPV) and true positive rate (TPR) of Tigmint-long. Table S11. Contiguity, correctness and benchmarking statistics for running LongStitch including the optional the ARKS-long step on human assemblies. Table S12. Summarizing the number of matching minimizers per ntLink-joined contig pair. Figure S1. Schematic describing gap size estimation algorithm in ntLink. Figure S2. Contiguity and correctness statistics of assemblies improved using LRScaf with different parameter combinations and LongStitch. Figure S3. Jupiter consistency plots showing the contiguity and correctness of LongStitch and LRScaf assemblies. Figure S4. Benchmarking results of improving assemblies with LongStitch, LRScaf or OPERA-LG. Figure S5. Contiguity and correctness results for each step the LongStitch pipeline, including the optional ARKS-long step, LRScaf and OPERA-LG on human assemblies. Figure S6. Benchmarking results for LRScaf and the LongStitch pipeline including the optional ARKS-long step on human assemblies. Figure S7. Time breakdown for each of the steps in LongStitch, including the optional ARKS-long step, and LRScaf. Figure S8. Contiguity and correctness results from sweeping on the ntLink k and w parameters for the default steps of LongStitch. Figure S9. Benchmarking results from sweeping on the ntLink k and w parameters for the default steps of LongStitch.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.268
Threshold uncertainty score0.382

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.005
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0050.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.7320.249

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.

Opus teacher head0.037
GPT teacher head0.266
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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