scholarly journals Hill number as a bacterial diversity measure framework with high-throughput sequence data

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Sanghoon Kang ◽  
Jorge L. M. Rodrigues ◽  
Justin P. Ng ◽  
Terry J. Gentry
2013 ◽  
Vol 5 (1) ◽  
pp. 21-25 ◽  
Author(s):  
Yue-Jian Hu ◽  
Qian Wang ◽  
Yun-Tao Jiang ◽  
Rui Ma ◽  
Wen-Wei Xia ◽  
...  

2009 ◽  
Vol 25 (19) ◽  
pp. 2607-2608 ◽  
Author(s):  
M. Morgan ◽  
S. Anders ◽  
M. Lawrence ◽  
P. Aboyoun ◽  
H. Pages ◽  
...  

2020 ◽  
Vol 9 (24) ◽  
Author(s):  
Sangam Kandel ◽  
Supaphen Sripiboon ◽  
Piroon Jenjaroenpun ◽  
David W. Ussery ◽  
Intawat Nookaew ◽  
...  

ABSTRACT Here, we present a 16S rRNA gene amplicon sequence data set and profiles demonstrating the bacterial diversity of baby and adult elephants from four different geographical locations in Thailand. The dominant phyla among baby and adult elephants were Bacteroidetes, Firmicutes, Proteobacteria, Kiritimatiellaeota, Euryarchaeota, and Tenericutes.


PLoS ONE ◽  
2020 ◽  
Vol 15 (4) ◽  
pp. e0230924
Author(s):  
Ao-Nan Xia ◽  
Jun Liu ◽  
Da-Cheng Kang ◽  
Hai-Guang Zhang ◽  
Ru-Hua Zhang ◽  
...  

2014 ◽  
Vol 490-491 ◽  
pp. 757-762
Author(s):  
Guo Li Ji ◽  
Long Teng Chen ◽  
Liang Liang Chen

This paper proposed a way of two-level parallel alignment based on sequence parallel vectorization with GPU acceleration on the Fermi architecture, which integrates sequence parallel vectorization, parallel k-means clustering approximate alignment and parallel Smith-Waterman algorithm. The method converts sequence alignment into vector alignment by first. Then it uses k-means alignment to divide sequences into several groups and reduce the size of sequence data. The expected accurate alignment result is achieved using parallel Smith-Waterman algorithm. The high-throughput mouse T-cell receptor (TCR) sequences were used to validate the proposed method. Under the same hardware condition, comparing to serial Smith-Waterman algorithm and CUDASW++2.0 algorithm, our method is the most efficient alignment algorithm with high alignment accuracy.


2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Antonio A. Ginart ◽  
Joseph Hui ◽  
Kaiyuan Zhu ◽  
Ibrahim Numanagić ◽  
Thomas A. Courtade ◽  
...  

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Yuka Torii ◽  
Kazuhiro Horiba ◽  
Satoshi Hayano ◽  
Taichi Kato ◽  
Takako Suzuki ◽  
...  

Abstract Background Kawasaki disease (KD) is an idiopathic systemic vasculitis that predominantly damages coronary arteries in children. Various pathogens have been investigated as triggers for KD, but no definitive causative pathogen has been determined. As KD is diagnosed by symptoms, several days are needed for diagnosis. Therefore, at the time of diagnosis of KD, the pathogen of the trigger may already be diminished. The aim of this study was to explore comprehensive pathogens in the sera at the acute stage of KD using high-throughput sequencing (HTS). Methods Sera of 12 patients at an extremely early stage of KD and 12 controls were investigated. DNA and RNA sequences were read separately using HTS. Sequence data were imported into the home-brew meta-genomic analysis pipeline, PATHDET, to identify the pathogen sequences. Results No RNA virus reads were detected in any KD case except for that of equine infectious anemia, which is known as a contaminant of commercial reverse transcriptase. Concerning DNA viruses, human herpesvirus 6B (HHV-6B, two cases) and Anelloviridae (eight cases) were detected among KD cases as well as controls. Multiple bacterial reads were obtained from KD and controls. Bacteria of the genera Acinetobacter, Pseudomonas, Delfita, Roseomonas, and Rhodocyclaceae appeared to be more common in KD sera than in the controls. Conclusion No single pathogen was identified in serum samples of patients at the acute phase of KD. With multiple bacteria detected in the serum samples, it is difficult to exclude the possibility of contamination; however, it is possible that these bacteria might stimulate the immune system and induce KD.


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