The emergence of next-generation sequencing (NGS) platforms imposes increasing demands on statistical methods and bioinformatic tools for the analysis and the management of the huge amounts of data generated by these technologies. Even at the early stages of their commercial availability, a large number of softwares already exist for analyzing NGS data. These tools can be fit into many general categories including alignment of sequence reads to a reference, base-calling and/or polymorphism detection, de novo assembly from paired or unpaired reads, structural variant detection and genome browsing. This manuscript aims to guide readers in the choice of the available computational tools that can be used to face the several steps of the data analysis workflow.

Bioinformatics for Next Generation Sequencing Data / Magi A.; Benelli M.; Gozzini A.; Girolami F.; Torricelli F.; Brandi M.L.. - In: GENES. - ISSN 2073-4425. - STAMPA. - (2010), pp. 294-307.

Bioinformatics for Next Generation Sequencing Data

MAGI, ALBERTO;BENELLI, MATTEO;BRANDI, MARIA LUISA
2010

Abstract

The emergence of next-generation sequencing (NGS) platforms imposes increasing demands on statistical methods and bioinformatic tools for the analysis and the management of the huge amounts of data generated by these technologies. Even at the early stages of their commercial availability, a large number of softwares already exist for analyzing NGS data. These tools can be fit into many general categories including alignment of sequence reads to a reference, base-calling and/or polymorphism detection, de novo assembly from paired or unpaired reads, structural variant detection and genome browsing. This manuscript aims to guide readers in the choice of the available computational tools that can be used to face the several steps of the data analysis workflow.
294
307
Magi A.; Benelli M.; Gozzini A.; Girolami F.; Torricelli F.; Brandi M.L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2158/780650
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