Measuring Reproducibility of High-Throughput Deep-Sequencing Experiments Based on Self-adaptive Mixture Copula

2013 ◽  
pp. 301-313
Author(s):  
Qian Zhang ◽  
Junping Zhang ◽  
Chenghai Xue
Keyword(s):  
High Throughput ◽  
Deep Sequencing ◽  
Self Adaptive

scholarly journals High-throughput deep sequencing reveals the important role that microRNAs play in the salt response in sweet potato (Ipomoea batatas L.)

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhengmei Yang ◽  
Panpan Zhu ◽  
Hunseung Kang ◽  
Lin Liu ◽  
Qinghe Cao ◽  
...  
Keyword(s):  
Sweet Potato ◽  
High Throughput ◽  
Deep Sequencing ◽  
Ipomoea Batatas ◽  
Salt Response

Deep sequencing and high-throughput analysis of PIWI-associated small RNAs

Methods ◽  
2017 ◽  
Vol 126 ◽  
pp. 66-75 ◽  
Author(s):  
Yuka W. Iwasaki ◽  
Kyoko Ishino ◽  
Haruhiko Siomi
Keyword(s):  
High Throughput ◽  
Deep Sequencing ◽  
Small Rnas ◽  
High Throughput Analysis ◽  
Throughput Analysis

scholarly journals From clinical sample to complete genome: Comparing methods for the extraction of HIV-1 RNA for high-throughput deep sequencing

2017 ◽  
Vol 239 ◽  
pp. 10-16 ◽  
Author(s):  
Marion Cornelissen ◽  
Astrid Gall ◽  
Monique Vink ◽  
Fokla Zorgdrager ◽  
Špela Binter ◽  
...  
Keyword(s):  
High Throughput ◽  
Deep Sequencing ◽  
Complete Genome ◽  
Clinical Sample ◽  
Hiv 1

scholarly journals Evaluation of direct metagenomics and target enriched approaches for high-throughput sequencing of field rabies viruses

2019 ◽  
Vol 63 (4) ◽  
pp. 471-479
Author(s):  
Anna Orłowska ◽  
Ewelina Iwan ◽  
Marcin Smreczak ◽  
Jerzy Rola
Keyword(s):  
High Throughput ◽  
Deep Sequencing ◽  
High Throughput Sequencing ◽  
De Novo ◽  
High Reliability ◽  
Rna Extraction ◽  
Genetic Material ◽  
Target Enrichment ◽  
Red Foxes ◽  
Field Samples

AbstractIntroductionHigh-throughput sequencing (HTS) identifies random viral fragments in environmental samples metagenomically. High reliability gains it broad application in virus evolution, host-virus interaction, and pathogenicity studies. Deep sequencing of field samples with content of host genetic material and bacteria often produces insufficient data for metagenomics and must be preceded by target enrichment. The main goal of the study was the evaluation of HTS for complete genome sequencing of field-case rabies viruses (RABVs).Material and MethodsThe material was 23 RABVs isolated mainly from red foxes and one European bat lyssavirus-1 isolate propagated in neuroblastoma cells. Three methods of RNA isolation were tested for the direct metagenomics and RABV-enriched approaches. Deep sequencing was performed with a MiSeq sequencer (Illumina) and reagent v3 kit. Bioinformatics data were evaluated by Kraken and Centrifuge software and de novo assembly was done with metaSPAdes.ResultsTesting RNA extraction procedures revealed the deep sequencing scope superiority of the combined TRIzol/column method. This HTS methodology made it possible to obtain complete genomes of all the RABV isolates collected in the field. Significantly greater rates of RABV genome coverages (over 5,900) were obtained with RABV enrichment. Direct metagenomic studies sequenced the full length of 6 out of 16 RABV isolates with a medium coverage between 1 and 71.ConclusionDirect metagenomics gives the most realistic illustration of the field sample microbiome, but with low coverage. For deep characterisation of viruses, e.g. for spatial and temporal phylogeography during outbreaks, target enrichment is recommended as it covers sequences much more completely.

scholarly journals Deep sequencing of HPV16 genomes: A new high-throughput tool for exploring the carcinogenicity and natural history of HPV16 infection

2015 ◽  
Vol 1 ◽  
pp. 3-11 ◽  
Author(s):  
Michael Cullen ◽  
Joseph F. Boland ◽  
Mark Schiffman ◽  
Xijun Zhang ◽  
Nicolas Wentzensen ◽  
...  
Keyword(s):  
Natural History ◽  
High Throughput ◽  
Deep Sequencing ◽  
History Of ◽  
Hpv16 Infection

scholarly journals Genome-Wide Identification of miRNAs Responsive to Drought in Peach (Prunus persica) by High-Throughput Deep Sequencing

PLoS ONE ◽  
2012 ◽  
Vol 7 (12) ◽  
pp. e50298 ◽  
Author(s):  
Vahap Eldem ◽  
Ufuk Çelikkol Akçay ◽  
Esma Ozhuner ◽  
Yakup Bakır ◽  
Serkan Uranbey ◽  
...  
Keyword(s):  
High Throughput ◽  
Deep Sequencing ◽  
Prunus Persica ◽  
Genome Wide

scholarly journals High-throughput deep sequencing shows that microRNAs play important roles in switchgrass responses to drought and salinity stress

2013 ◽  
Vol 12 (3) ◽  
pp. 354-366 ◽  
Author(s):  
Fuliang Xie ◽  
Charles Neal Stewart ◽  
Faten A. Taki ◽  
Qiuling He ◽  
Huawei Liu ◽  
...  
Keyword(s):  
Salinity Stress ◽  
High Throughput ◽  
Deep Sequencing

scholarly journals A high-throughput RNA-seq approach to profile transcriptional responses

2015 ◽  
Author(s):  
Gregory A Moyerbrailean ◽  
Gordon O Davis ◽  
Chris T Harvey ◽  
Donovan Watza ◽  
Xiaoquan Wen ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Deep Sequencing ◽  
Transcriptome Profiling ◽  
Iterative Refinement ◽  
Specific Gene ◽  
Rna Seq ◽  
Transcriptional Responses ◽  
Expression Screening

In recent years, different technologies have been used to measure genome-wide gene expression levels and to study the transcriptome across many types of tissues and in response to in vitro treatments. However, a full understanding of gene regulation in any given cellular and environmental context combination is still missing. This is partly because analyzing tissue/environment-specific gene expression generally implies screening a large number of cellular conditions and samples, without prior knowledge of which conditions are most informative (e.g. some cell types may not respond to certain treatments). To circumvent these challenges, we have established a new two-step high-throughput and cost-effective RNA-seq approach: the first step consists of gene expression screening of a large number of conditions, while the second step focuses on deep sequencing of the most relevant conditions (e.g. largest number of differentially expressed genes). This study design allows for a fast and economical screen in step one, with a more profitable allocation of resources for the deep sequencing of re-pooled libraries in step two. We have applied this approach to study the response to 26 treatments in three lymphoblastoid cell line samples and we show that it is applicable for other high-throughput transcriptome profiling requiring iterative refinement or screening.

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