scholarly journals A survey of sequence alignment algorithms for next-generation sequencing

2010 ◽  
Vol 11 (5) ◽  
pp. 473-483 ◽  
Author(s):  
H. Li ◽  
N. Homer
Keyword(s):  
Next Generation Sequencing ◽  
Sequence Alignment ◽  
Next Generation ◽  
Alignment Algorithms ◽  
Generation Sequencing

scholarly journals Evaluation and Comparison of Multiple Aligners for Next-Generation Sequencing Data Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Jing Shang ◽  
Fei Zhu ◽  
Wanwipa Vongsangnak ◽  
Yifei Tang ◽  
Wenyu Zhang ◽  
...  
Keyword(s):  
Data Analysis ◽  
Next Generation Sequencing ◽  
Real Life ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Computational Performance ◽  
Alignment Algorithms ◽  
Ngs Data Analysis ◽  
Ngs Data ◽  
Generation Sequencing

Next-generation sequencing (NGS) technology has rapidly advanced and generated the massive data volumes. To align and map the NGS data, biologists often randomly select a number of aligners without concerning their suitable feature, high performance, and high accuracy as well as sequence variations and polymorphisms existing on reference genome. This study aims to systematically evaluate and compare the capability of multiple aligners for NGS data analysis. To explore this capability, we firstly performed alignment algorithms comparison and classification. We further used long-read and short-read datasets from both real-life andin silicoNGS data for comparative analysis and evaluation of these aligners focusing on three criteria, namely, application-specific alignment feature, computational performance, and alignment accuracy. Our study demonstrated the overall evaluation and comparison of multiple aligners for NGS data analysis. This serves as an important guiding resource for biologists to gain further insight into suitable selection of aligners for specific and broad applications.

scholarly journals HIVE-Hexagon: High-Performance, Parallelized Sequence Alignment for Next-Generation Sequencing Data Analysis

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e99033 ◽  
Author(s):  
Luis Santana-Quintero ◽  
Hayley Dingerdissen ◽  
Jean Thierry-Mieg ◽  
Raja Mazumder ◽  
Vahan Simonyan
Keyword(s):  
Data Analysis ◽  
Next Generation Sequencing ◽  
Sequence Alignment ◽  
High Performance ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Generation Sequencing ◽  
Sequencing Data Analysis

Labordiagnostik bei gastrointestinalen Tumoren

2020 ◽  
Vol 11 (05) ◽  
pp. 232-238
Author(s):  
Marcus Kleber
Keyword(s):  
Next Generation Sequencing ◽  
Kolorektales Karzinom ◽  
Next Generation ◽  
Generation Sequencing

ZUSAMMENFASSUNGDas kolorektale Karzinom (KRK) ist einer der häufigsten malignen Tumoren in Deutschland. Einer frühzeitigen Diagnostik kommt große Bedeutung zu. Goldstandard ist hier die Koloskopie. Die aktuelle S3-Leitlinie Kolorektales Karzinom empfiehlt zum KRK-Screening den fäkalen okkulten Bluttest. Für das Monitoring von Patienten vor und nach Tumorresektion werden die Messung des Carcinoembryonalen Antigens (CEA) und der Mikrosatellitenstabilität empfohlen. Für die Auswahl der korrekten Chemotherapie scheint derzeit eine Überprüfung des Mutationsstatus, mindestens des KRAS-Gens und des BRAF-Gens, sinnvoll zu sein. Eine Reihe an neuartigen Tumormarkern befindet sich momentan in der Entwicklung, hat jedoch noch nicht die Reife für eine mögliche Anwendung in der Routinediagnostik erreicht. Den schnellsten Weg in die breite Anwendung können Next-Generation-Sequencing-basierte genetische Tests finden.

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