An online copy number variant detectionmethod for short sequencing reads
Yazarlar (4)
Ayten Yiğiter Hacettepe Üniversitesi, Türkiye
Jie Chen Augusta University, Amerika Birleşik Devletleri
Lingling An Department Of Biosystems Engineering, Amerika Birleşik Devletleri
Dr. Öğr. Üyesi Nazan DANACIOĞLU Sinop Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Journal of Applied Statistics (Q4) | ||
| Dergi ISSN | 0266-4763 Dergi Bilgileri (2015) | ||
| Dergi Tarandığı Indeksler | SSCI | ||
| Makale Dili | İngilizce | Basım Tarihi | 07-2015 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 28-01-2015 |
| Cilt / Sayı / Sayfa | 42 / 7 / 1556–1571 | DOI | 10.1080/02664763.2014.1001330 |
| Makale Linki | http://www.tandfonline.com/doi/full/10.1080/02664763.2014.1001330 | ||
| UAK Araştırma Alanları |
İstatistiksel Deney Tasarımı
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| Özet |
| The availability of the next generation sequencing (NGS) technology in today's biomedical research has provided new opportunities in scientific discovery of genetic information. The high-throughput NGS technology, especially DNA-seq, is particularly useful in profiling a genome for the analysis of DNA copy number variants (CNVs). The read count (RC) data resulting from NGS technology are massive and information rich. How to exploit the RC data for accurate CNV detection has become a computational and statistical challenge. We provide a statistical online change point method to help detect CNVs in the sequencing RC data in this paper. This method uses the idea of online searching for change point (or breakpoint) with a Markov chain assumption on the breakpoints loci and an iterative computing process via a Bayesian framework. We illustrate that an online change-point detection method is particularly … |
| Anahtar Kelimeler |
| Bayesian estimate | change point (or breakpoint) | DNA copy number variation | next generation sequencing | online change-point detection method |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 6 |
| Scopus | 5 |
| Google Scholar | 7 |