Sentence examples for sequences were removed using from inspiring English sources

Sequence reads from all samples were cleaned using the FASTX toolkit (http://hannonlab.cshl.edu/fastx_toolkit/). First all the reads containing 'N' were discarded using a perl script, then adapter sequences were removed using the fastx_clipper program, followed by removal of quality < 5 bases from the 3′ end with fastq_quality_trimmer, requiring a minimum sequence length of 50 bp.

FASTQ files were cleaned by primer removal using CutAdapt 1.6 and de-replicated, and low-quality sequences were removed using PrinSeq-lite v0.20.

Sequences were grouped into operational taxonomic units (OTUs) based on 97% sequence identity, and chimeric sequences were removed, using UPARSE60.

Short reads (<20 bp) and adaptor sequences were removed using TrimGalore (version 0.4.4 24, cutadapt version 1.1425, and Python 2.7.8, with fastqc command (version 0.11.3).

The adaptors and low quality sequences were removed using Trimmomatic v0.30 (Bolger et al. 2014).

Redundant amino acid sequences were removed using CD-hit [22] with a 95% sequence identity cut-off.

Sequences with missing data were removed from the database by manual inspection using MEGA4 v4.1, and redundant sequences were removed using the NRDB program (http://pubmlst.org/perl/mlstanalyse/mlstanalyse.pl?site=pubmlst&page=nrdb&referer=pubmlst.org).org

Vector sequences were removed using Cross_match.

Adapter sequences were removed using Cutadapt [ 23].

Chimeric sequences were removed using Usearch.

Redundancies between sequences were removed using custom Perl scripts.