A better sequence-read simulator program for metagenomics.

ABSTRACT:

Background

There are many programs available for generating simulated whole-genome shotgun sequence reads. The data generated by many of these programs follow predefined models, which limits their use to the authors' original intentions. For example, many models assume that read lengths follow a uniform or normal distribution. Other programs generate models from actual sequencing data, but are limited to reads from single-genome studies. To our knowledge, there are no programs that allow a user to generate simulated data following non-parametric read-length distributions and quality profiles based on empirically-derived information from metagenomics sequencing data.

Results

We present BEAR (Better Emulation for Artificial Reads), a program that uses a machine-learning approa

SUBMITTER: Johnson S 

PROVIDER: S-EPMC4168713 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature