scholarly journals Haplotype assignment of longitudinal viral deep-sequencing data using co-variation of variant frequencies

2018 ◽  
Author(s):  
Juanita Pang ◽  
Cristina Venturini ◽  
Asif U. Tamuri ◽  
Sunando Roy ◽  
Judith Breuer ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Evolutionary Dynamics ◽  
Synthetic Data ◽  
Data Sets ◽  
Haplotype Reconstruction ◽  
Sequencing Data ◽  
New Approach ◽  
Deep Sequencing Data ◽  
Genomic Element ◽  
Haplotype Assignment

ABSTRACTLongitudinal deep sequencing of viruses can provide detailed information about intra-host evolutionary dynamics including how viruses interact with and transmit between hosts. Many analyses require haplotype reconstruction, identifying which variants are co-located on the same genomic element. Most current methods to perform this reconstruction are based on a high density of variants and cannot perform this reconstruction for slowly evolving viruses. We present a new approach, HaROLD (HAplotype Reconstruction Of Longitudinal Deep sequencing data), which performs this reconstruction based on identifying co-varying variant frequencies using a probabilistic framework. We test this method with synthetic data sets of mixed cytomegalovirus and norovirus genomes, demonstrating high accuracy when longitudinal samples are available.

scholarly journals Evolutionary dynamics and molecular epidemiology of West Nile virus in New York State: 1999–2015

2019 ◽  
Vol 5 (2) ◽  
Author(s):  
Sean M Bialosuknia ◽  
Yi Tan ◽  
Steven D Zink ◽  
Cheri A Koetzner ◽  
Joseph G Maffei ◽  
...  
Keyword(s):  
New York ◽  
West Nile Virus ◽  
Deep Sequencing ◽  
Evolutionary Dynamics ◽  
New York State ◽  
Rapid Expansion ◽  
Sequencing Data ◽  
West Nile ◽  
York State ◽  
Deep Sequencing Data

AbstractFollowing its introduction into New York State (NYS) in 1999, West Nile virus (WNV; Flavivirus, Flaviviridae) underwent a rapid expansion throughout the USA and into Canada and Latin America. WNV has been characterized as being evolutionarily stable, with weak geographic structure, a dominance of purifying selection and limited adaptive change. We analyzed all available full-genome WNV sequences, focusing on the 543 available sequences from NYS, which included 495 newly sequenced 2000–15 isolates. In addition, we analyzed deep-sequencing data from 317 of these isolates. While our data are generally in agreement with the limited pace of evolutionary change and broad geographic and temporal mixing identified in other studies, we have identified some important exceptions. Most notably, there are 14 codons which demonstrated evidence of positive selection as determined by multiple models, including some positions with evidence of selection in NYS exclusively. Coincident with increased WNV activity, genotypes possessing one or more of these mutations, designated NY01, NY07, and NY10, have increased in prevalence in recent years and displaced historic strains. In addition, we have found a geographical bias with many of these mutations, which suggests selective pressures and adaptations could be regional. Lastly, our deep-sequencing data suggest both increased overall diversity in avian tissue isolates relative to mosquito isolates and multiple non-synonymous minority variants that are both host-specific and retained over time and space. Together, these data provide novel insight into the evolutionary pressures on WNV and the need for continued genetic surveillance and characterization of emergent strains.

scholarly journals Frequency-based haplotype reconstruction from deep sequencing data of bacterial populations

2015 ◽  
Vol 43 (16) ◽  
pp. e105-e105 ◽  
Author(s):  
Sergio Pulido-Tamayo ◽  
Aminael Sánchez-Rodríguez ◽  
Toon Swings ◽  
Bram Van den Bergh ◽  
Akanksha Dubey ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Haplotype Reconstruction ◽  
Sequencing Data ◽  
Bacterial Populations ◽  
Deep Sequencing Data

scholarly journals GenomeGems: evaluation of genetic variability from deep sequencing data

2012 ◽  
Vol 5 (1) ◽  
pp. 338
Author(s):  
Sharon Ben-Zvi ◽  
Adi Givati ◽  
Noam Shomron
Keyword(s):  
Genetic Variability ◽  
Deep Sequencing ◽  
Sequencing Data ◽  
Deep Sequencing Data

Considering DNA damage when interpreting mtDNA heteroplasmy in deep sequencing data

2017 ◽  
Vol 26 ◽  
pp. 1-11 ◽  
Author(s):  
Molly M. Rathbun ◽  
Jennifer A. McElhoe ◽  
Walther Parson ◽  
Mitchell M. Holland
Keyword(s):  
Dna Damage ◽  
Deep Sequencing ◽  
Sequencing Data ◽  
Deep Sequencing Data

Quasi-2D inversion of DCR and TDEM data for shallow investigations

Geophysics ◽  
2011 ◽  
Vol 76 (4) ◽  
pp. F239-F250 ◽  
Author(s):  
Fernando A. Monteiro Santos ◽  
Hesham M. El-Kaliouby
Keyword(s):  
Joint Inversion ◽  
Synthetic Data ◽  
Data Sets ◽  
Complex Environments ◽  
Inversion Algorithm ◽  
2D Inversion ◽  
New Approach ◽  
Earth Models ◽  
Time Domain Electromagnetic ◽  
Inversion Techniques

Joint or sequential inversion of direct current resistivity (DCR) and time-domain electromagnetic (TDEM) data commonly are performed for individual soundings assuming layered earth models. DCR and TDEM have different and complementary sensitivity to resistive and conductive structures, making them suitable methods for the application of joint inversion techniques. This potential joint inversion of DCR and TDEM methods has been used by several authors to reduce the ambiguities of the models calculated from each method separately. A new approach for joint inversion of these data sets, based on a laterally constrained algorithm, was found. The method was developed for the interpretation of soundings collected along a line over a 1D or 2D geology. The inversion algorithm was tested on two synthetic data sets, as well as on field data from Saudi Arabia. The results show that the algorithm is efficient and stable in producing quasi-2D models from DCR and TDEM data acquired in relatively complex environments.

scholarly journals Analyzing the microRNA Transcriptome in Plants Using Deep Sequencing Data

Biology ◽  
2012 ◽  
Vol 1 (2) ◽  
pp. 297-310 ◽  
Author(s):  
Xiaozeng Yang ◽  
Lei Li
Keyword(s):  
Deep Sequencing ◽  
Sequencing Data ◽  
Deep Sequencing Data

scholarly journals Discovery of Novel Human Breast Cancer MicroRNAs from Deep Sequencing Data by Analysis of Pri-MicroRNA Secondary Structures

PLoS ONE ◽  
2011 ◽  
Vol 6 (2) ◽  
pp. e16403 ◽  
Author(s):  
Seongho Ryu ◽  
Natasha Joshi ◽  
Kevin McDonnell ◽  
Jongchan Woo ◽  
Hyejin Choi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Deep Sequencing ◽  
Human Breast Cancer ◽  
Secondary Structures ◽  
Human Breast ◽  
Sequencing Data ◽  
Deep Sequencing Data
Sign in / Sign up

Export Citation Format

Share Document