Zseq: An Approach for Preprocessing Next-Generation Sequencing Data.

ABSTRACT: Next-generation sequencing technology generates a huge number of reads (short sequences), which contain a vast amount of genomic data. The sequencing process, however, comes with artifacts. Preprocessing of sequences is mandatory for further downstream analysis. We present Zseq, a linear method that identifies the most informative genomic sequences and reduces the number of biased sequences, sequence duplications, and ambiguous nucleotides. Zseq finds the complexity of the sequences by counting the number of unique k-mers in each sequence as its corresponding score and also takes into the account other factors such as ambiguous nucleotides or high GC-content percentage in k-mers. Based on a z-score threshold, Zseq sweeps through the sequences again and filters those with a z-score less tha

SUBMITTER: Alkhateeb A 

PROVIDER: S-EPMC5563921 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature