02217nas a2200349 4500008004100000022001400041245009500055210006900150260001500219300000900234490000700243520109300250100002301343700001801366700001901384700002201403700002301425700001601448700002701464700001901491700001501510700001601525700001801541700001901559700001301578700001501591700001801606700001701624700002601641710007101667856012901738 2021 eng d a2041-172300aOrchestrating and sharing large multimodal data for transparent and reproducible research.0 aOrchestrating and sharing large multimodal data for transparent c2021 10 04 a57970 v123 a
Reproducibility is essential to open science, as there is limited relevance for findings that can not be reproduced by independent research groups, regardless of its validity. It is therefore crucial for scientists to describe their experiments in sufficient detail so they can be reproduced, scrutinized, challenged, and built upon. However, the intrinsic complexity and continuous growth of biomedical data makes it increasingly difficult to process, analyze, and share with the community in a FAIR (findable, accessible, interoperable, and reusable) manner. To overcome these issues, we created a cloud-based platform called ORCESTRA ( orcestra.ca ), which provides a flexible framework for the reproducible processing of multimodal biomedical data. It enables processing of clinical, genomic and perturbation profiles of cancer samples through automated processing pipelines that are user-customizable. ORCESTRA creates integrated and fully documented data objects with persistent identifiers (DOI) and manages multiple dataset versions, which can be shared for future studies.
1 aMammoliti, Anthony1 aSmirnov, Petr1 aNakano, Minoru1 aSafikhani, Zhaleh1 aEeles, Christopher1 aSeo, Heewon1 aNair, Sisira, Kadambat1 aMer, Arvind, S1 aSmith, Ian1 aHo, Chantal1 aBeri, Gangesh1 aKusko, Rebecca1 aLin, Eva1 aYu, Yihong1 aMartin, Scott1 aHafner, Marc1 aHaibe-Kains, Benjamin1 aMassive Analysis Quality Control (MAQC) Society Board of Directors uhttps://www.clinbioinfosspa.es/content/orchestrating-and-sharing-large-multimodal-data-transparent-and-reproducible-research05180nas a2201117 4500008004100000022001400041245011300055210006900168260001200237300001200249490000700261520174900268653001402017653003102031653001502062653002502077653001902102653005102121653001102172653002902183653003802212653001102250653000902261653002302270653003602293653002702329100002202356700001702378700002402395700002802419700003302447700002702480700001502507700002402522700002902546700002602575700002802601700001702629700002002646700002102666700001902687700002702706700001902733700002002752700002402772700003002796700001902826700002602845700002902871700001802900700002102918700002202939700003202961700002002993700002603013700002903039700002103068700002203089700002103111700001903132700002703151700002403178700002903202700003203231700002003263700001803283700003103301700002803332700001603360700002503376700003103401700003303432700002903465700002203494700002103516700002403537700001903561700002503580700001703605700001703622700001803639700002303657700002003680700001603700700002203716700002503738700001803763700002303781700002003804700002003824700002103844700003303865700001703898700002103915856012603936 2020 eng d a1468-624400aOptimised molecular genetic diagnostics of Fanconi anaemia by whole exome sequencing and functional studies.0 aOptimised molecular genetic diagnostics of Fanconi anaemia by wh c2020 04 a258-2680 v573 aPURPOSE: Patients with Fanconi anaemia (FA), a rare DNA repair genetic disease, exhibit chromosome fragility, bone marrow failure, malformations and cancer susceptibility. FA molecular diagnosis is challenging since FA is caused by point mutations and large deletions in 22 genes following three heritability patterns. To optimise FA patients' characterisation, we developed a simplified but effective methodology based on whole exome sequencing (WES) and functional studies.
METHODS: 68 patients with FA were analysed by commercial WES services. Copy number variations were evaluated by sequencing data analysis with RStudio. To test missense variants, wt FANCA cDNA was cloned and variants were introduced by site-directed mutagenesis. Vectors were then tested for their ability to complement DNA repair defects of a FANCA-KO human cell line generated by TALEN technologies.
RESULTS: We identified 93.3% of mutated alleles including large deletions. We determined the pathogenicity of three FANCA missense variants and demonstrated that two variants reported in mutations databases as 'affecting functions' are SNPs. Deep analysis of sequencing data revealed patients' true mutations, highlighting the importance of functional analysis. In one patient, no pathogenic variant could be identified in any of the 22 known FA genes, and in seven patients, only one deleterious variant could be identified (three patients each with FANCA and FANCD2 and one patient with FANCE mutations) CONCLUSION: WES and proper bioinformatics analysis are sufficient to effectively characterise patients with FA regardless of the rarity of their complementation group, type of mutations, mosaic condition and DNA source.
10aCell Line10aDNA Copy Number Variations10aDNA Repair10aDNA-Binding Proteins10aFanconi Anemia10aFanconi Anemia Complementation Group A Protein10aFemale10aGene Knockout Techniques10aGenetic Predisposition to Disease10aHumans10aMale10aMutation, Missense10aPolymorphism, Single Nucleotide10awhole exome sequencing1 aBogliolo, Massimo1 aPujol, Roser1 aAza-Carmona, Miriam1 aMuñoz-Subirana, Núria1 aRodriguez-Santiago, Benjamin1 aCasado, José, Antonio1 aRio, Paula1 aBauser, Christopher1 aReina-Castillón, Judith1 aLopez-Sanchez, Marcos1 aGonzalez-Quereda, Lidia1 aGallano, Pia1 aCatalá, Albert1 aRuiz-Llobet, Ana1 aBadell, Isabel1 aDiaz-Heredia, Cristina1 aHladun, Raquel1 aSenent, Leonort1 aArgiles, Bienvenida1 aBurgues, Juan, Miguel Ber1 aBañez, Fatima1 aArrizabalaga, Beatriz1 aAlmaraz, Ricardo, López1 aLopez, Monica1 aFiguera, Ángela1 aMolinés, Antonio1 ade Soto, Inmaculada, Pérez1 aHernando, Inés1 aMuñoz, Juan, Antonio1 aMarin, Maria, Del Rosari1 aBalmaña, Judith1 aStjepanovic, Neda1 aCarrasco, Estela1 aCuesta, Isabel1 aCosuelo, José, Miguel1 aRegueiro, Alexandra1 aJimenez, José, Moraleda1 aGalera-Miñarro, Ana, Maria1 aRosiñol, Laura1 aCarrió, Anna1 aBeléndez-Bieler, Cristina1 aSoto, Antonio, Escudero1 aCela, Elena1 ade la Mata, Gregorio1 aFernández-Delgado, Rafael1 aGarcia-Pardos, Maria, Carmen1 aSáez-Villaverde, Raquel1 aBarragaño, Marta1 aPortugal, Raquel1 aLendinez, Francisco1 aHernadez, Ines1 aVagace, José, Manue1 aTapia, Maria1 aNieto, José1 aGarcia, Marta1 aGonzalez, Macarena1 aVicho, Cristina1 aGalvez, Eva1 aValiente, Alberto1 aAntelo, Maria, Luisa1 aAncliff, Phil1 aGarcía, Francisco1 aDopazo, Joaquin1 aSevilla, Julian1 aPaprotka, Tobias1 aPérez-Jurado, Luis, Alberto1 aBueren, Juan1 aSurralles, Jordi uhttps://www.clinbioinfosspa.es/content/optimised-molecular-genetic-diagnostics-fanconi-anaemia-whole-exome-sequencing-and01646nas a2200217 4500008004100000245007200041210006900113300001000182490000800192520083200200653001501032653002101047653007301068653002601141653004201167653005901209100001501268700002401283700001501307856010601322 2006 eng d00aOntology-driven approaches to analyzing data in functional genomics0 aOntologydriven approaches to analyzing data in functional genomi a67-860 v3163 aOntologies are fundamental knowledge representations that provide not only standards for annotating and indexing biological information, but also the basis for implementing functional classification and interpretation models. This chapter discusses the application of gene ontology (GO) for predictive tasks in functional genomics. It focuses on the problem of analyzing functional patterns associated with gene products. This chapter is divided into two main parts. The first part overviews GO and its applications for the development of functional classification models. The second part presents two methods for the characterization of genomic information using GO. It discusses methods for measuring functional similarity of gene products, and a tool for supporting gene expression clustering analysis and validation.
10ababelomics10aCluster Analysis10aCluster Analysis Computational Biology/*methods *Data Interpretation10aComputational Biology10aStatistical Gene Expression Profiling10aStatistical Gene Expression Profiling *Genomics Humans1 aAzuaje, F.1 aAl-Shahrour, Fatima1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1667140102737nas a2200181 4500008004100000245005300041210005300094300000600147490000600153520218900159100001802348700001302366700002102379700001602400700001402416700001902430856010602449 2006 eng d00aOrigin and evolution of the peroxisomal proteome0 aOrigin and evolution of the peroxisomal proteome a80 v13 aBACKGROUND: Peroxisomes are ubiquitous eukaryotic organelles involved in various oxidative reactions. Their enzymatic content varies between species, but the presence of common protein import and organelle biogenesis systems support a single evolutionary origin. The precise scenario for this origin remains however to be established. The ability of peroxisomes to divide and import proteins post-translationally, just like mitochondria and chloroplasts, supports an endosymbiotic origin. However, this view has been challenged by recent discoveries that mutant, peroxisome-less cells restore peroxisomes upon introduction of the wild-type gene, and that peroxisomes are formed from the Endoplasmic Reticulum. The lack of a peroxisomal genome precludes the use of classical analyses, as those performed with mitochondria or chloroplasts, to settle the debate. We therefore conducted large-scale phylogenetic analyses of the yeast and rat peroxisomal proteomes. RESULTS : Our results show that most peroxisomal proteins (39-58%) are of eukaryotic origin, comprising all proteins involved in organelle biogenesis or maintenance. A significant fraction (13-18%), consisting mainly of enzymes, has an alpha-proteobacterial origin and appears to be the result of the recruitment of proteins originally targeted to mitochondria. Consistent with the findings that peroxisomes are formed in the Endoplasmic Reticulum, we find that the most universally conserved Peroxisome biogenesis and maintenance proteins are homologous to proteins from the Endoplasmic Reticulum Assisted Decay pathway. CONCLUSION: Altogether our results indicate that the peroxisome does not have an endosymbiotic origin and that its proteins were recruited from pools existing within the primitive eukaryote. Moreover the reconstruction of primitive peroxisomal proteomes suggests that ontogenetically as well as phylogenetically, peroxisomes stem from the Endoplasmic Reticulum. REVIEWERS: This article was reviewed by Arcady Mushegian, Gaspar Jekely and John Logsdon. OPEN PEER REVIEW: Reviewed by Arcady Mushegian, Gaspar Jekely and John Logsdon. For the full reviews, please go to the Reviewers’ comments section.1 aGabaldón, T.1 aSnel, B.1 avan Zimmeren, F.1 aHemrika, W.1 aTabak, H.1 aHuynen, M., A. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1655631400404nas a2200121 4500008004100000245003900041210003900080260003500119300001100154100002400165700001500189856007800204 2005 eng d00aOntologies and functional genomics0 aOntologies and functional genomics bWiley, F. Azuaje and J. Dopazo a99-1021 aAl-Shahrour, Fatima1 aDopazo, J. uhttps://www.clinbioinfosspa.es/content/ontologies-and-functional-genomics