Published in

Oxford University Press (OUP), Bioinformatics, 12(26), p. i343-i349

DOI: 10.1093/bioinformatics/btq184

Links

Tools

Export citation

Search in Google Scholar

VARiD: A variation detection framework for color-space and letter-space platforms

Journal article published in 2010 by Adrian Vasile Dalca ORCID, Stephen M. Rumble, Samuel Levy, Michael Brudno
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Upload
Green circle
Postprint: archiving allowed
Upload
Red circle
Published version: archiving forbidden
Policy details
Data provided by SHERPA/RoMEO

Abstract

Motivation: High-throughput sequencing (HTS) technologies are transforming the study of genomic variation. The various HTS technologies have different sequencing biases and error rates, and while most HTS technologies sequence the residues of the genome directly, generating base calls for each position, the Applied Biosystem's SOLiD platform generates dibase-coded (color space) sequences. While combining data from the various platforms should increase the accuracy of variation detection, to date there are only a few tools that can identify variants from color space data, and none that can analyze color space and regular (letter space) data together.