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Deep Sequencing Data Analysis

Overview of attention for book
Attention for Chapter 13: Detection of Reverse Transcriptase Termination Sites Using cDNA Ligation and Massive Parallel Sequencing
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Chapter title
Detection of Reverse Transcriptase Termination Sites Using cDNA Ligation and Massive Parallel Sequencing
Chapter number 13
Book title
Deep Sequencing Data Analysis
Published in
Methods in molecular biology, January 2013
DOI 10.1007/978-1-62703-514-9_13
Pubmed ID
Book ISBNs
978-1-62703-513-2, 978-1-62703-514-9
Authors

Lukasz J. Kielpinski, Mette Boyd, Albin Sandelin, Jeppe Vinther, Kielpinski, Lukasz J., Boyd, Mette, Sandelin, Albin, Vinther, Jeppe

Abstract

Detection of reverse transcriptase termination sites is important in many different applications, such as structural probing of RNAs, rapid amplification of cDNA 5' ends (5' RACE), cap analysis of gene expression, and detection of RNA modifications and protein-RNA cross-links. The throughput of these methods can be increased by applying massive parallel sequencing technologies.Here, we describe a versatile method for detection of reverse transcriptase termination sites based on ligation of an adapter to the 3' end of cDNA with bacteriophage TS2126 RNA ligase (CircLigase™). In the following PCR amplification, Illumina adapters and index sequences are introduced, thereby allowing amplicons to be pooled and sequenced on the standard Illumina platform for genomic DNA sequencing. Moreover, we demonstrate how to map sequencing reads and perform analysis of the sequencing data with freely available tools that do not require formal bioinformatics training. As an example, we apply the method to detection of transcription start sites in mouse liver cells.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 6%
Denmark 1 6%
Germany 1 6%
Unknown 14 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 29%
Researcher 3 18%
Student > Bachelor 2 12%
Student > Master 2 12%
Student > Doctoral Student 1 6%
Other 3 18%
Unknown 1 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 53%
Biochemistry, Genetics and Molecular Biology 8 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 08 November 2013.
All research outputs
#18,353,475
of 22,729,647 outputs
Outputs from Methods in molecular biology
#7,855
of 13,086 outputs
Outputs of similar age
#218,076
of 280,769 outputs
Outputs of similar age from Methods in molecular biology
#220
of 341 outputs
Altmetric has tracked 22,729,647 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,086 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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 280,769 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 341 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.