MersV1, Main, Exploration, bibRecord, 000B14

Zseq: An Approach for Preprocessing Next-Generation Sequencing Data

Identifieur interne : 000B14 ( Main/Exploration ); précédent : 000B13; suivant : 000B15

Zseq: An Approach for Preprocessing Next-Generation Sequencing Data

Auteurs : Abedalrhman Alkhateeb ; Luis Rueda

Source :

Journal of Computational Biology [ 1066-5277 ] ; 2017.

RBID : PMC:5563921

Descripteurs français

KwdFr :
- Algorithmes, Analyse de séquence d'ADN (), Génome humain, Génomique (), Humains, Logiciel, Séquençage nucléotidique à haut débit ().
MESH :
- Algorithmes, Analyse de séquence d'ADN, Génome humain, Génomique, Humains, Logiciel, Séquençage nucléotidique à haut débit.

English descriptors

KwdEn :
- Algorithms, Genome, Human, Genomics (methods), High-Throughput Nucleotide Sequencing (methods), Humans, Sequence Analysis, DNA (methods), Software.
MESH :
- methods : Genomics, High-Throughput Nucleotide Sequencing, Sequence Analysis, DNA.
- Algorithms, Genome, Human, Humans, Software.

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 uniquek-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 ink-mers. Based on az-score threshold, Zseq sweeps through the sequences again and filters those with a z-score less than the user-defined threshold.

Zseq algorithm is able to provide a better mapping rate; it reduces the number of ambiguous bases significantly in comparison with other methods. Evaluation of the filtered reads has been conducted by aligning the reads and assembling the transcripts using the reference genome as well as de novo assembly. The assembled transcripts show a better discriminative ability to separate cancer and normal samples in comparison with another state-of-the-art method. Moreover, de novo assembled transcripts from the reads filtered by Zseq have longer genomic sequences than other tested methods. Estimating the threshold of the cutoff point is introduced using labeling rules with optimistic results.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5563921

DOI: 10.1089/cmb.2017.0021
PubMed: 28414515
PubMed Central: 5563921

Affiliations:

Le document en format XML

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<p><bold>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</bold>
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<p><bold>Zseq algorithm is able to provide a better mapping rate; it reduces the number of ambiguous bases significantly in comparison with other methods. Evaluation of the filtered reads has been conducted by aligning the reads and assembling the transcripts using the reference genome as well as <italic>de novo</italic>
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 assembled transcripts from the reads filtered by Zseq have longer genomic sequences than other tested methods. Estimating the threshold of the cutoff point is introduced using labeling rules with optimistic results.</bold>
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Zseq: An Approach for Preprocessing Next-Generation Sequencing Data

Zseq: An Approach for Preprocessing Next-Generation Sequencing Data

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

Pour générer des pages wiki

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