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

Overview of attention for article published in BMC Genomics, July 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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2 patents

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132 Dimensions

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305 Mendeley
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Title
Elimination of PCR duplicates in RNA-seq and small RNA-seq using unique molecular identifiers
Published in
BMC Genomics, July 2018
DOI 10.1186/s12864-018-4933-1
Pubmed ID
Authors

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

Abstract

RNA-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. We 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. Using 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.

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X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 305 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 305 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 62 20%
Student > Ph. D. Student 52 17%
Student > Master 33 11%
Student > Bachelor 30 10%
Other 14 5%
Other 37 12%
Unknown 77 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 109 36%
Agricultural and Biological Sciences 54 18%
Medicine and Dentistry 12 4%
Immunology and Microbiology 10 3%
Computer Science 6 2%
Other 30 10%
Unknown 84 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 March 2022.
All research outputs
#2,725,573
of 23,400,864 outputs
Outputs from BMC Genomics
#894
of 10,761 outputs
Outputs of similar age
#56,380
of 327,798 outputs
Outputs of similar age from BMC Genomics
#28
of 203 outputs
Altmetric has tracked 23,400,864 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,761 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 327,798 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 203 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.