Next Generation Sequencing: Approach for Assessment and enrichment of raw data

Authors

  • Jyoti Kant Choudhari Chhattisgarh Swami Vivekananda Technical University, Bhilai (C.G) India
  • Jyotsna Choubey Sub-DIC Bioinformatics, National Institute of Technology Raipur (C.G.) India
  • Ashish Patel Sub-DIC Bioinformatics, National Institute of Technology Raipur (C.G.) India

DOI:

https://doi.org/10.30732/ijbbb.20170202001

Keywords:

Next Generating Sequencing, Sequence Quality, FASTQ, Galaxy server

Abstract

Next-generation sequencing (NGS) is a non-sanger technique based on high-throughput capacity for determining the exact order of nucleotide in the given DNA & RNA molecule. Modern high-throughput sequencer’s produce millions of sequences read in a single run. The quality of these data are not perfect because they contains artefacts like poor quality reads, adapter contamination, wrong base calls and INDELs due to instrument failure or chemical process error. In this study, a procedure has been designed for the refinement and improvement of quality of NGS data for further biological processes.

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Published

2017-09-14

How to Cite

Choudhari, J. K., Choubey, J., & Patel, A. (2017). Next Generation Sequencing: Approach for Assessment and enrichment of raw data. CSVTU International Journal of Biotechnology, Bioinformatics and Biomedical, 2(2), 25–32. https://doi.org/10.30732/ijbbb.20170202001

Issue

Vol. 2 No. 2 (2017): Peer Review

Section

Articles

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