Evidence map›Paper›PMID 30001700›Full record

ArticleBMC genomics2018

Elimination of PCR duplicates in RNA-seq and small RNA-seq using unique molecular identifiers.

Yu Fu, Pei-Hsuan Wu, Timothy Beane, Phillip D Zamore, Zhiping Weng

Abstract read
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers.

0numbers the graph read from it
0cells of the map it votes in
106citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

106 citing papers in PubMed.

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46 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yu FuBioinformatics Program, Boston University, 44 Cummington Mall, Boston, MA, 02215, USA.
Pei-Hsuan WuRNA Therapeutics Institute and Howard Hughes Medical Institute, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA, 01605, USA.
Timothy BeaneRNA Therapeutics Institute and Howard Hughes Medical Institute, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA, 01605, USA.
Phillip D ZamoreRNA Therapeutics Institute and Howard Hughes Medical Institute, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA, 01605, USA. phillip.zamore@umassmed.edu.ORCID http://orcid.org/0000-0002-4505-9618
Zhiping WengProgram in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA, 01605, USA. zhiping.weng@umassmed.edu.

Funding

Understanding the architecture, regulation, and function of piRNA-producing genesP01HD078253 · NICHD · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI WENG, ZHIPING · 2015 to 2019
$6.5M
Understanding the Mechanism of RNA InterferenceR37GM062862 · NIGMS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI ZAMORE, PHILLIP D · 2010 to 2019
$5.3M
Eunice Kennedy Shriver National Institute of Child Health and Human Development HD078253National Institute of General Medical Sciences R37GM062862NICHD NIH HHS P01 HD078253NIGMS NIH HHS R37 GM062862
6 · The paper itself

Abstract

backgroundRNA-seq and small RNA-seq are powerful, quantitative tools to study gene regulation and function. Common high-throughput sequencing methods rely on polymerase chain reaction (PCR) to expand the starting material, but not every molecule amplifies equally, causing some to be overrepresented. Unique molecular identifiers (UMIs) can be used to distinguish undesirable PCR duplicates derived from a single molecule and identical but biologically meaningful reads from different molecules.

resultsWe have incorporated UMIs into RNA-seq and small RNA-seq protocols and developed tools to analyze the resulting data. Our UMIs contain stretches of random nucleotides whose lengths sufficiently capture diverse molecule species in both RNA-seq and small RNA-seq libraries generated from mouse testis. Our approach yields high-quality data while allowing unique tagging of all molecules in high-depth libraries.

conclusionsUsing simulated and real datasets, we demonstrate that our methods increase the reproducibility of RNA-seq and small RNA-seq data. Notably, we find that the amount of starting material and sequencing depth, but not the number of PCR cycles, determine PCR duplicate frequency. Finally, we show that computational removal of PCR duplicates based only on their mapping coordinates introduces substantial bias into data analysis.

Indexed as

AnimalsGene LibraryMaleMicePolymerase Chain ReactionReproducibility of ResultsRNASequence Analysis, RNATestisRNAPCR cyclePCR duplicatesRibognomeRNA-seqSequencing depthSmall RNA-seqStarting materialTranscriptomeUMIUnique molecular identifier

Identifiers

PMID30001700
PMCPMC6044086

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.