000284812 001__ 284812
000284812 005__ 20240229155056.0
000284812 0247_ $$2doi$$a10.1093/bioinformatics/btad633
000284812 0247_ $$2pmid$$apmid:37851409
000284812 0247_ $$2ISSN$$a0266-7061
000284812 0247_ $$2ISSN$$a1367-4803
000284812 0247_ $$2ISSN$$a1367-4811
000284812 0247_ $$2ISSN$$a1460-2059
000284812 0247_ $$2altmetric$$aaltmetric:155652580
000284812 037__ $$aDKFZ-2023-02111
000284812 041__ $$aEnglish
000284812 082__ $$a570
000284812 1001_ $$0P:(DE-HGF)0$$aWeber, Thomas$$b0$$eFirst author
000284812 245__ $$aMosaiCatcher v2: a single-cell structural variations detection and analysis reference framework based on Strand-seq.
000284812 260__ $$aOxford$$bOxford Univ. Press$$c2023
000284812 3367_ $$2DRIVER$$aarticle
000284812 3367_ $$2DataCite$$aOutput Types/Journal article
000284812 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1699358880_10420
000284812 3367_ $$2BibTeX$$aARTICLE
000284812 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000284812 3367_ $$00$$2EndNote$$aJournal Article
000284812 500__ $$a#EA:B480#LA:B480# / 2023 Nov 1;39(11):btad633
000284812 520__ $$aSingle-cell DNA template strand sequencing (Strand-seq) allows a range of various genomic analysis including chromosome length haplotype phasing and structural variation (SV) calling in individual cells. Here, we present MosaiCatcher v2, a standardised workflow and reference framework for single-cell SV detection using Strand-seq. This framework introduces a range of functionalities, including: an automated upstream Quality Control (QC) and assembly sub-workflow that relies on multiple genome assemblies and incorporates a multistep normalisation module, integration of the scNOVA SV functional characterization and of the ArbiGent SV genotyping modules, platform portability, as well as a user-friendly and shareable web report. These new features of MosaiCatcher v2 enable reproducible computational processing of Strand-seq data, which are increasingly used in human genetics and single cell genomics, towards production environments. MosaiCatcher v2 is compatible with both container and conda environments, ensuring reproducibility and robustness and positioning the framework as a cornerstone in computational processing of Strand-seq data.MosaiCatcher v2 is a standardised workflow, implemented using the Snakemake workflow management system. The pipeline is available on GitHub: https://github.com/friendsofstrandseq/mosaicatcher-pipeline/ and on the snakemake-workflow-catalog: https://snakemake.github.io/snakemake-workflow-catalog/?usage=friendsofstrandseq/mosaicatcher-pipeline. Strand-seq example input data used in the publication can be found in the Data availability statement. Additionally, a lightweight dataset for test purposes can be found on the GitHub repository.Supplementary data are available at Bioinformatics online.
000284812 536__ $$0G:(DE-HGF)POF4-312$$a312 - Funktionelle und strukturelle Genomforschung (POF4-312)$$cPOF4-312$$fPOF IV$$x0
000284812 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
000284812 7001_ $$0P:(DE-He78)10a9b063005cea37559ebbb0142d23d0$$aCosenza, Marco Raffaele$$b1
000284812 7001_ $$0P:(DE-He78)372b77c2acf8604690a6a325a4e89287$$aKorbel, Jan$$b2$$eLast author$$udkfz
000284812 773__ $$0PERI:(DE-600)1468345-3$$a10.1093/bioinformatics/btad633$$gp. btad633$$n11$$pbtad633$$tBioinformatics$$v39$$x0266-7061$$y2023
000284812 909CO $$ooai:inrepo02.dkfz.de:284812$$pVDB
000284812 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-HGF)0$$aDeutsches Krebsforschungszentrum$$b0$$kDKFZ
000284812 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)10a9b063005cea37559ebbb0142d23d0$$aDeutsches Krebsforschungszentrum$$b1$$kDKFZ
000284812 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)372b77c2acf8604690a6a325a4e89287$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000284812 9131_ $$0G:(DE-HGF)POF4-312$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vFunktionelle und strukturelle Genomforschung$$x0
000284812 9141_ $$y2023
000284812 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2023-07-11T10:36:43Z
000284812 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2023-07-11T10:36:43Z
000284812 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Anonymous peer review$$d2023-07-11T10:36:43Z
000284812 915__ $$0LIC:(DE-HGF)CCBYNV$$2V:(DE-HGF)$$aCreative Commons Attribution CC BY (No Version)$$bDOAJ$$d2023-07-11T10:36:43Z
000284812 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2023-08-31
000284812 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2023-08-31
000284812 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2023-08-31
000284812 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2023-08-31
000284812 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2023-08-31
000284812 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2023-10-21$$wger
000284812 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2023-10-21
000284812 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2023-10-21
000284812 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central$$d2023-10-21
000284812 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2023-10-21
000284812 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2023-10-21
000284812 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2023-10-21
000284812 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences$$d2023-10-21
000284812 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bBIOINFORMATICS : 2022$$d2023-10-21
000284812 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2023-10-21
000284812 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2023-10-21
000284812 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bBIOINFORMATICS : 2022$$d2023-10-21
000284812 9202_ $$0I:(DE-He78)B480-20160331$$kB480$$lMechanismen der genetischen Variation und Datenwissenschaft$$x0
000284812 9201_ $$0I:(DE-He78)B480-20160331$$kB480$$lMechanismen der genetischen Variation und Datenwissenschaft$$x0
000284812 9200_ $$0I:(DE-He78)B480-20160331$$kB480$$lMechanismen der genetischen Variation und Datenwissenschaft$$x0
000284812 980__ $$ajournal
000284812 980__ $$aVDB
000284812 980__ $$aI:(DE-He78)B480-20160331
000284812 980__ $$aUNRESTRICTED