Open Access Highly Accessed Research article

Assessment of whole genome amplification-induced bias through high-throughput, massively parallel whole genome sequencing

Robert Pinard1, Alex de Winter1, Gary J Sarkis1, Mark B Gerstein2, Karrie R Tartaro1, Ramona N Plant1, Michael Egholm1, Jonathan M Rothberg1 and John H Leamon1*

Author Affiliations

1 454 Life Sciences, 20 Commercial Street, Branford CT 06405, USA

2 MB&B Department, Yale University, 266 Whitney Ave., New Haven CT 06520, USA

For all author emails, please log on.

BMC Genomics 2006, 7:216  doi:10.1186/1471-2164-7-216

Published: 23 August 2006

Additional files

Additional File 1:

Table S1. Read distributions between unamplified Halobacterium samples. Kolmogorov-Smirnov comparison of the distributions of reads per bin from an unamplified sample of Halobacterium species NRC-1 with four replicate unamplified control libraries. Bin Size refers to the number of bases comprising each individual bin into which the genome was broken for analysis; 100,000 reads were used for each analysis. As no significant differences were found between the distributions, ranked bias values (derived from D statistics) were assumed equivalent and not assigned. Table S2. Read distributions between unamplified Campylobacter samples. Kolmogorov-Smirnov comparison of the distributions of reads per bin from an unamplified sample of Campylobacter jejuni with four replicate unamplified control libraries. Bin Size refers to the number of bases comprising each individual bin into which the genome was broken for analysis; 100,000 reads were used for each analysis. As no significant differences were found between the distributions, ranked bias values (derived from D statistics) were assumed equivalent and not assigned.

Format: DOC Size: 93KB Download file

This file can be viewed with: Microsoft Word Viewer

Open Data