Title
NeatFreq: reference-free data reduction and coverage normalization for De Novo sequence assembly.
Abstract
Deep shotgun sequencing on next generation sequencing (NGS) platforms has contributed significant amounts of data to enrich our understanding of genomes, transcriptomes, amplified single-cell genomes, and metagenomes. However, deep coverage variations in short-read data sets and high sequencing error rates of modern sequencers present new computational challenges in data interpretation, including mapping and de novo assembly. New lab techniques such as multiple displacement amplification (MDA) of single cells and sequence independent single primer amplification (SISPA) allow for sequencing of organisms that cannot be cultured, but generate highly variable coverage due to amplification biases.
Year
DOI
Venue
2014
10.1186/s12859-014-0357-3
BMC Bioinformatics
Keywords
Field
DocType
microarrays,bioinformatics,algorithms
Massive parallel sequencing,Multiple displacement amplification,Shotgun sequencing,Deep sequencing,Biology,Genomics,Single cell sequencing,DNA sequencing,Bioinformatics,Genetics,Sequence assembly
Journal
Volume
Issue
ISSN
15
1
1471-2105
Citations 
PageRank 
References 
8
0.47
4
Authors
6