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JBrowseR: an R interface to the JBrowse 2 genome browser

2021· article· en· W3174992442 on OpenAlexaff
Elliot A. Hershberg, Garrett Stevens, Colin Diesh, Peter Xie, Teresa De Jesus Martinez, Robert Buels, Lincoln Stein, Ian Holmes

Bibliographic record

VenueBioinformatics · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsOntario Institute for Cancer Research
FundersNational Institute of General Medical SciencesNational Cancer InstituteNational Human Genome Research InstituteNational Institutes of Health
KeywordsGenome browserComputer scienceInterface (matter)Web browserVariety (cybernetics)VisualizationDownloadWorld Wide WebSource codeGenomeUser interfaceSoftwareCode (set theory)The InternetGenomicsOperating systemBiologyProgramming languageSet (abstract data type)GeneticsData mining

Abstract

fetched live from OpenAlex

MOTIVATION: Genome browsers are an essential tool in genome analysis. Modern genome browsers enable complex and interactive visualization of a wide variety of genomic data modalities. While such browsers are very powerful, they can be challenging to configure and program for bioinformaticians lacking expertise in web development. RESULTS: We have developed an R package that provides an interface to the JBrowse 2 genome browser. The package can be used to configure and customize the browser entirely with R code. The browser can be deployed from the R console, or embedded in Shiny applications or R Markdown documents. AVAILABILITY AND IMPLEMENTATION: JBrowseR is available for download from CRAN, and the source code is openly available from the Github repository at https://github.com/GMOD/JBrowseR/.

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)0.010
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: Software
Teacher disagreement score0.137
Threshold uncertainty score0.457

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.031
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0080.006
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.1370.220

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 head0.013
GPT teacher head0.246
Teacher spread0.233 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreSoftware

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".

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Citations26
Published2021
Admission routes1
Has abstractyes

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