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

Abstract

Background

Single-cell RNA-sequencing (scRNA-seq) experiments typically analyze hundreds or thousands of cells after amplification of the cDNA. The high throughput is made possible by the early introduction of sample-specific bar codes (BCs), and the amplification bias is alleviated by unique molecular identifiers (UMIs). Thus, the ideal analysis pipeline for scRNA-seq data needs to efficiently tabulate reads according to both BC and UMI.

Findings

zUMIs is a pipeline that can handle both known and random BCs and also efficiently collapse UMIs, either just for exon mapping reads or for both exon and intron mapping reads. If BC annotation is missing, zUMIs can accurately detect intact cells from the distribution of sequencing reads. Another unique feature of zUMIs is the adaptive downsampling function that facilitates dealing with hugely varying library sizes but also allows the user to evaluate whether the library has been sequenced to saturation. To illustrate the utility of zUMIs, we analyzed a single-nucleus RNA-seq dataset and show that more than 35% of all reads map to introns. Also, we show that these intronic reads are informative about expression levels, significantly increasing the number of detected genes and improving the cluster resolution.

Conclusions

zUMIs flexibility makes if possible to accommodate data generated with any of the major scRNA-seq protocols that use BCs and UMIs and is the most feature-rich, fast, and user-friendly pipeline to process such scRNA-seq data.

Now published in GigaScience doi: 10.1093/gigascience/giy059

Swati Parekh 1Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, 82152 Martinsried, GermanyFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Swati ParekhChristoph Ziegenhain 1Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, 82152 Martinsried, GermanyFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Christoph ZiegenhainBeate Vieth 1Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, 82152 Martinsried, GermanyFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Beate ViethWolfgang Enard 1Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, 82152 Martinsried, GermanyFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteInes Hellmann 1Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, 82152 Martinsried, GermanyFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Ines Hellmann

A version of this preprint has been published in the Open Access journal GigaScience (see paper https://doi.org/10.1093/gigascience/giy059 ), where the paper and peer reviews are published openly under a CC-BY 4.0 license.

These peer reviews were as follows:

Reviewer 1: http://dx.doi.org/10.5524/REVIEW.101183 Reviewer 2: http://dx.doi.org/10.5524/REVIEW.101184

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

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Abstract

Background

Findings

Conclusions

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