Abstract 839: Whole genome DNA methylation analysis of multiple myeloma identifies pervasive hypomethylation and biomarkers of survival

Author(s):  
Benjamin G. Barwick ◽  
Doris R. Powell ◽  
Daniel Penaherrera ◽  
Sheri Skerget ◽  
Jonathan J. Keats ◽  
...  
2019 ◽  
Author(s):  
Benjamin G. Barwick ◽  
Doris R. Powell ◽  
Daniel Penaherrera ◽  
Sheri Skerget ◽  
Jonathan J. Keats ◽  
...  

Epigenomics ◽  
2016 ◽  
Vol 8 (8) ◽  
pp. 1061-1077 ◽  
Author(s):  
Hae Min Jeong ◽  
Sangseon Lee ◽  
Heejoon Chae ◽  
RyongNam Kim ◽  
Mi Jeong Kwon ◽  
...  

SLEEP ◽  
2016 ◽  
Vol 39 (4) ◽  
pp. 743-755 ◽  
Author(s):  
Yung-Che Chen ◽  
Ting-Wen Chen ◽  
Mao-Chang Su ◽  
Chung-Jen Chen ◽  
Kuang-Den Chen ◽  
...  

2018 ◽  
Author(s):  
Haoyu Cheng ◽  
Yun Xu

AbstractAs a gold-standard technique for DNA methylation analysis, whole-genome bisulfite sequencing (WGBS) helps researchers to study the genome-wide DNA methylation at single-base resolution. However, aligning WGBS reads to the large reference genome is a major computational bottleneck in DNA methylation analysis projects. Although several WGBS aligners have been developed in recent years, it is difficult for them to efficiently process the ever-increasing bisulfite sequencing data. Here we propose BitMapperBS, an ultrafast and memory-efficient aligner that is designed for WGBS reads. To improve the performance of BitMapperBS, we propose various strategies specifically for the challenges that are unique to the WGBS aligners, which are ignored in most existing methods. Our experiments on real and simulated datasets show that BitMapperBS is one order of magnitude faster than the state-of-the-art WGBS aligners, while achieves similar or better sensitivity and precision. BitMapperBS is freely available at https://github.com/chhylp123/BitMapperBS.


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