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Data released on May 14, 2018

Supporting data for "zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs"

Parekh, S; Ziegenhain, C; Vieth, B; Enard, W; Hellmann, I (2018): Supporting data for "zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs" GigaScience Database. http://dx.doi.org/10.5524/100447 RIS BibTeX Text

Single cell RNA-seq (scRNA-seq) experiments typically analyze hundreds or thousands of cells after amplication of the cDNA. The high throughput is made possible by the early introduction of sample-specific barcodes (BCs) and the amplication bias is alleviated by unique molecular identiers (UMIs). Thus the ideal analysis pipeline for scRNA-seq data needs to efficiently tabulate reads according to both BC and UMI. zUMIs is such a pipeline, it can handle both known and random BCs and also efficiently collapses UMIs, either just for Exon mapping reads or for both Exon and Intron mapping reads. Another unique feature of zUMIs is the adaptive downsampling function, that facilitates dealing with hugely varying library sizes, but also allows to evaluate whether the library has been sequenced to saturation. zUMIs flexibility allows to accommodate data generated with any of the major scRNA-seq protocols that use BCs and UMIs. To illustrate the utility of zUMIs, we analysed a single-nucleus RNA-seq dataset and show that more than 35% of all reads map to Introns. We furthermore show that these intronic reads are informative about expression levels, significantly increasing the number of detected genes and improving the cluster resolution.

Contact Submitter

Additional information:

https://github.com/sdparekh/zUMIs

https://scicrunch.org/resolver/RRID:SCR_016139

Keywords:

single-cell rna-sequencing digital gene expression unique molecular identifiers pipeline 

Software, Workflow, Transcriptomic

http://gigadb.org/images/data/cropped/100447.jpg

Funding:

  • Funding body - Deutsche Forschungsgemeinschaft
  • Award ID - SFB1243-A15
  • Awardee - I Hellmann
  • Funding body - Deutsche Forschungsgemeinschaft
  • Award ID - SFB1243-A14
  • Awardee - W Enard

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File NameSample IDData TypeFile FormatSizeRelease Date 
mixed archivearchive198.31 MB2018-04-30
Mixed archiveTAR67 GB2018-05-15
ReadmeTEXT1.71 KB2018-04-30
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