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231225s2017 xx |||||o 00| ||eng c |
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|a 10.1080/02664763.2016.1158798
|2 doi
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|a eng
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| 100 |
1 |
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|a Yang, Shengping
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Beta approximation of ratio distribution and its application to next generation sequencing read counts
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| 264 |
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|c 2017
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Revised 20.11.2019
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a Paired sequencing data are commonly collected in genomic studies to control biological variation. However, existing data processing strategies suffer at low coverage regions, which are unavoidable due to the limitation of current sequencing technology. Furthermore, information contained in the absolute values of the read counts is commonly ignored. We propose a read count ratio processing/modification method, to not only incorporate information contained in the absolute values of paired counts into one variable, but also mitigate the discrete artifact, especially when both counts are small. Simulation shows that the processed variable fits well with a Beta distribution, thus providing an easy tool for down-stream inference analysis
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|a Journal Article
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|a Beta distribution
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| 650 |
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|a Next-generation sequencing
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| 650 |
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|a Paired tumor and normal tissues
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| 650 |
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|a Primary 62E17
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| 650 |
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|a Ratio of counts
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| 650 |
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4 |
|a Statistical artifacts
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| 650 |
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4 |
|a secondary 62P10
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| 700 |
1 |
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|a Fang, Zhide
|e verfasserin
|4 aut
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|i Enthalten in
|t Journal of applied statistics
|d 1991
|g 44(2017), 1 vom: 01., Seite 57-70
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|x 0266-4763
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| 773 |
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|g volume:44
|g year:2017
|g number:1
|g day:01
|g pages:57-70
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|u http://dx.doi.org/10.1080/02664763.2016.1158798
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