Literature DB >> 30204482

EasyQC: Tool with Interactive User Interface for Efficient Next-Generation Sequencing Data Quality Control.

Vijaya Raghavan Rangamaran1, Bharathram Uppili2, Dharani Gopal1, Kirubagaran Ramalingam1.   

Abstract

The advent of next-generation sequencing (NGS) technologies has revolutionized the world of genomic research. Millions of sequences are generated in a short period of time and they provide intriguing insights to the researcher. Many NGS platforms have evolved over a period of time and their efficiency has been ever increasing. Still, primarily because of the chemistry, glitch in the sequencing machine and human handling errors, some artifacts tend to exist in the final sequence data set. These sequence errors have a profound impact on the downstream analyses and may provide misleading information. Hence, filtering of these erroneous reads has become inevitable and myriad of tools are available for this purpose. However, many of them are accessible as a command line interface that requires the user to enter each command manually. Here, we report EasyQC, a tool for NGS data quality control (QC) with a graphical user interface providing options to carry out trimming of NGS reads based on quality, length, homopolymer, and ambiguous bases. EasyQC also possesses features such as format converter, paired end merger, adapter trimmer, and a graph generator that generates quality distribution, length distribution, GC content, and base composition graphs. Comparison of raw and processed sequence data sets using EasyQC suggested significant increase in overall quality of the sequences. Testing of EasyQC using NGS data sets on a standalone desktop proved to be relatively faster. EasyQC is developed using PERL modules and can be executed in Windows and Linux platforms. With the various QC features, easy interface for end users, and cross-platform compatibility, EasyQC would be a valuable addition to the already existing tools facilitating better downstream analyses.

Entities:  

Keywords:  NGS; downstream processing; graphical interface; quality control

Mesh:

Year:  2018        PMID: 30204482     DOI: 10.1089/cmb.2017.0186

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  1 in total

1.  Vertical Microbial Profiling of Arabian Sea Oxygen Minimal Zone Reveals Complex Bacterial Communities and Distinct Functional Implications.

Authors:  Vijaya Raghavan Rangamaran; Sai H Sankara Subramanian; Karpaga Raja Sundari Balachandran; Dharani Gopal
Journal:  Microb Ecol       Date:  2022-02-23       Impact factor: 4.552

  1 in total

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