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Comparison of two high-throughput semiconductor chip sequencing platforms in noninvasive prenatal testing for Down syndrome in early pregnancy

Overview of attention for article published in BMC Medical Genomics, April 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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3 tweeters
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2 Facebook pages

Citations

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9 Dimensions

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30 Mendeley
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Title
Comparison of two high-throughput semiconductor chip sequencing platforms in noninvasive prenatal testing for Down syndrome in early pregnancy
Published in
BMC Medical Genomics, April 2016
DOI 10.1186/s12920-016-0182-9
Pubmed ID
Authors

Sunshin Kim, HeeJung Jung, Sung Hee Han, SeungJae Lee, JeongSub Kwon, Min Gyun Kim, Hyungsik Chu, Hongliang Chen, Kyudong Han, Hwanjong Kwak, Sunghoon Park, Hee Jae Joo, Byung Chul Kim, Jong Bhak

Abstract

Noninvasive prenatal testing (NIPT) to detect fetal aneuploidy using next-generation sequencing on ion semiconductor platforms has become common. There are several sequencers that can generate sufficient DNA reads for NIPT. However, the approval criteria vary among platforms and countries. This can delay the introduction of such devices and systems to clinics. A comparison of the sensitivity and specificity of two different platforms using the same sequencing chemistry could be useful in NIPT for fetal chromosomal aneuploidies. This would improve healthcare authorities' confidence in decision-making on sequencing-based tests. One hundred and one pregnant women who were predicted at high risk of fetal defects using conventional prenatal screening tests, and who underwent definitive diagnosis by full karyotyping, were enrolled from three hospitals in Korea. Most of the pregnant women (69.79 %) received NIPT during weeks 11-13 of gestation and 30.21 % during weeks 14-18. We used Ion Torrent PGM and Proton semi-conductor-based sequencers with 0.3× sequencing coverage depth. The average total reads of 101 samples were approximately 4.5 and 7.6 M for PGM and Proton, respectively. A Burrows-Wheeler Aligner (BWA) algorithm was used for the alignment, and a z-score was used to decide fetal trisomy 21. Interactive dot diagrams from the sequencing data showed minimal z-score values of 2.07 and 2.10 to discriminate negative versus positive cases of fetal trisomy 21 for the two different sequencing systems. Our z-score-based discrimination method resulted in 100 % positive and negative prediction values for both ion semiconductor PGM and Proton sequencers, regardless of their sequencing chip and chemistry differences. Both platforms performed well at an early stage (11-13 weeks of gestation) compared with previous studies. These results suggested that, using two different sequencers, NIPT to detect fetal trisomy 21 in early pregnancy is accurate and platform-independent. The data suggested that the amount of sequencing and the application of common, simple, and robust statistical analyses are more important than sequencing chemistry and platform types. This result has practical implications in countries where PGM is approved for NIPT but the Proton system is not.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 3%
Unknown 29 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 20%
Other 5 17%
Student > Master 4 13%
Student > Bachelor 2 7%
Student > Doctoral Student 2 7%
Other 5 17%
Unknown 6 20%
Readers by discipline Count As %
Medicine and Dentistry 6 20%
Agricultural and Biological Sciences 5 17%
Biochemistry, Genetics and Molecular Biology 3 10%
Nursing and Health Professions 3 10%
Philosophy 1 3%
Other 4 13%
Unknown 8 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 06 May 2016.
All research outputs
#2,925,635
of 7,659,635 outputs
Outputs from BMC Medical Genomics
#148
of 415 outputs
Outputs of similar age
#91,994
of 266,366 outputs
Outputs of similar age from BMC Medical Genomics
#4
of 13 outputs
Altmetric has tracked 7,659,635 research outputs across all sources so far. This one has received more attention than most of these and is in the 61st percentile.
So far Altmetric has tracked 415 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 62% 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 266,366 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.