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Record W2604200516 · doi:10.1101/123455

CiliaCarta: an integrated and validated compendium of ciliary genes

2017· preprint· en· W2604200516 on OpenAlexaff
Teunis J. P. van Dam, Julie Kennedy, Robin van der Lee, Erik de Vrieze, Kirsten A. Wunderlich, Suzanne Rix, Gerard W. Dougherty, Nils J. Lambacher, Chunmei Li, Victor L. Jensen, Michel R. Leroux, Rim Hjeij, Nicola Horn, Yves Texier, Yasmin Wissinger, Jeroen van Reeuwijk, Gabrielle Wheway, Barbara Knapp, Jan Frederik Scheel, Brunella Franco, Dorus A. Mans, Erwin van Wijk, François Képès, Gisela G. Slaats, Grischa Toedt, Hannie Kremer, Heymut Omran, Katarzyna Szymańska, Konstantinos Koutroumpas, Marius Ueffing, Thanh-Minh T. Nguyen, Stef J.F. Letteboer, Machteld M. Oud, Sylvia E. C. van Beersum, Miriam Schmidts, Philip L. Beales, Qianhao Lu, Rachel H. Giles, Radek Szklarczyk, Robert B. Russell, Toby J. Gibson, Colin A. Johnson, Oliver E. Blacque, Uwe Wolfrum, Karsten Boldt, Ronald Roepman, Víctor Hernández-Hernández, Martijn A. Huynen

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2017
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCiliopathyCiliopathiesCiliumBiologyCandidate geneJoubert syndromeGeneComputational biologyPhenotypeCompendiumGeneticsZebrafishBioinformatics

Abstract

fetched live from OpenAlex

Abstract The cilium is an essential organelle at the surface of most mammalian cells whose dysfunction causes a wide range of genetic diseases collectively called ciliopathies. The current rate at which new ciliopathy genes are identified suggests that many ciliary components remain undiscovered. We generated and rigorously analyzed genomic, proteomic, transcriptomic and evolutionary data and systematically integrated these using Bayesian statistics into a predictive score for ciliary function. This resulted in 285 candidate ciliary genes. We found experimental evidence of ciliary associations for 24 out of 36 analyzed candidate proteins. In addition, we show that OSCP1, which has previously been implicated in two distinct non-ciliary functions, causes a cilium dysfunction phenotype when depleted in zebrafish. The candidate list forms the basis of CiliaCarta, a comprehensive ciliary compendium covering 836 genes. The resource can be used to objectively prioritize candidate genes in whole exome or genome sequencing of ciliopathy patients and can be accessed at http://bioinformatics.bio.uu.nl/john/syscilia/ciliacarta/ .

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)0.005
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: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.004

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 head0.014
GPT teacher head0.236
Teacher spread0.223 · 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
GenreDataset

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

Citations14
Published2017
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicGenetic and Kidney Cyst DiseasesFrench-language works237,207