scholarly journals Comparing Ease of Programming in C++, Go, and Java for Implementing a Next-Generation Sequencing Tool

2019 ◽  
Vol 15 ◽  
pp. 117693431986901
Author(s):  
Pascal Costanza ◽  
Charlotte Herzeel ◽  
Wilfried Verachtert

elPrep is an extensible multithreaded software framework for efficiently processing Sequence Alignment/Map (SAM)/Binary Alignment/Map (BAM) files in next-generation sequencing pipelines. Similar to other SAM/BAM tools, a key challenge in elPrep is memory management, as such programs need to manipulate large amounts of data. We therefore investigated 3 programming languages with support for assisted or automated memory management for implementing elPrep, namely C++, Go, and Java. We implemented a nontrivial subset of elPrep in all 3 programming languages and compared them by benchmarking their runtime performance and memory use to determine the best language in terms of computational performance. In a previous article, we motivated why, based on these results, we eventually selected Go as our implementation language. In this article, we discuss the difficulty of achieving the best performance in each language in terms of programming language constructs and standard library support. While benchmarks are easy to objectively measure and evaluate, this is less obvious for assessing ease of programming. However, because we expect elPrep to be regularly modified and extended, this is an equally important aspect. We illustrate representative examples of challenges in all 3 languages, and give our opinion why we think that Go is a reasonable choice also in this light.

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Jing Shang ◽  
Fei Zhu ◽  
Wanwipa Vongsangnak ◽  
Yifei Tang ◽  
Wenyu Zhang ◽  
...  

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.


2020 ◽  
Vol 11 (05) ◽  
pp. 232-238
Author(s):  
Marcus Kleber

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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