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Targeted next generation sequencing of RB1 gene for the molecular diagnosis of Retinoblastoma

Overview of attention for article published in BMC Cancer, April 2015
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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 (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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6 X users
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2 patents
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1 Facebook page

Citations

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37 Dimensions

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39 Mendeley
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Title
Targeted next generation sequencing of RB1 gene for the molecular diagnosis of Retinoblastoma
Published in
BMC Cancer, April 2015
DOI 10.1186/s12885-015-1340-8
Pubmed ID
Authors

Bharanidharan Devarajan, Logambiga Prakash, Thirumalai Raj Kannan, Aloysius A Abraham, Usha Kim, Veerappan Muthukkaruppan, Ayyasamy Vanniarajan

Abstract

The spectrum of RB1gene mutations in Retinoblastoma (RB) patients and the necessity of multiple traditional methods for complete variant analysis make the molecular diagnosis a cumbersome, labor-intensive and time-consuming process. Here, we have used targeted next generation sequencing (NGS) approach with in-house analysis pipeline to explore its potential for the molecular diagnosis of RB. Thirty-three patients with RB and their family members were selected randomly. DNA from patient blood and/or tumor was used for RB1 gene targeted sequencing. The raw reads were obtained from Illumina Miseq. An in-house bioinformatics pipeline was developed to detect both single nucleotide variants (SNVs) and small insertions/deletions (InDels) and to distinguish between somatic and germline mutations. In addition, ExomeCNV and Cn. MOPS were used to detect copy number variations (CNVs). The pathogenic variants were identified with stringent criteria, and were further confirmed by conventional methods and cosegregation in families. Using our approach, an array of pathogenic variants including SNVs, InDels and CNVs were detected in 85% of patients. Among the variants detected, 63% were germline and 37% were somatic. Interestingly, nine novel pathogenic variants (33%) were also detected in our study. We demonstrated for the first time that targeted NGS is an efficient approach for the identification of wide spectrum of pathogenic variants in RB patients. This study is helpful for the molecular diagnosis of RB in a comprehensive and time-efficient manner.

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X Demographics

The data shown below were collected from the profiles of 6 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Pakistan 1 3%
Unknown 38 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 21%
Student > Master 6 15%
Student > Bachelor 5 13%
Student > Ph. D. Student 5 13%
Professor > Associate Professor 3 8%
Other 5 13%
Unknown 7 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 26%
Agricultural and Biological Sciences 10 26%
Medicine and Dentistry 6 15%
Nursing and Health Professions 1 3%
Computer Science 1 3%
Other 1 3%
Unknown 10 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 24 January 2019.
All research outputs
#3,118,499
of 22,800,560 outputs
Outputs from BMC Cancer
#701
of 8,297 outputs
Outputs of similar age
#42,406
of 264,516 outputs
Outputs of similar age from BMC Cancer
#33
of 257 outputs
Altmetric has tracked 22,800,560 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,297 research outputs from this source. They receive a mean Attention Score of 4.3. 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 264,516 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 83% of its contemporaries.
We're also able to compare this research output to 257 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.