We anticipate that this tool will be extremely useful for initial file processing, quality control and format conversion in sequencing based clinical and genomic research studies for expert and not-expert users.ĬlinQC is an open-source, easy-to-use and integrated tool, which facilitates the analysis of Sanger and NGS sequencing data in a single platform with a common input output model. We have developed ClinQC, a flexible, integrated and easy-to-use solution for sequencing data processing, format conversion and quality control for Sanger and three NGS platforms including Illumina, 454 and Ion Torrent.
#Sanger sequence analysis software
Therefore, a one-stop, integrated and easy-to-use software tool to analyze Sanger as well as NGS sequencing data is needed, which offers easy handling of input and output data and support analysis of multiple sample/patients in a single run. Many of these tools work only for a particular NGS sequencing platform, are limited in their functionality (such as specific input format requirements) and none supports Sanger sequencing format conversion, quality control, trimming and base calling. Īt present, several solutions are available for NGS data quality control such as NGS QC Toolkit, FastQC, PRINSEQ, TagDust, FASTX-Toolkit, SolexaQA, TagCleaner, CANGS, ngs_backbone, Galaxy, SIMPLEX and QC-Chain. Moreover, they should be able to analyze several sample/patients data generated from both Sanger and NGS platforms in a single run and provide execution flexibility by using requirement based customized parameters. Therefore, integrated software tools are required, which can eliminate platform specific sequencing errors as well as low quality reads, and perform format conversion, quality trimming and filtering. In order to identify the potential disease causing mutations with great accuracy, it is essential to use only high quality reads. While NGS technologies have been used to identify variants in several patients in a cost and time effective manner, Sanger sequencing has been used as a complementary method to narrow down and confirm the NGS-detected variants before making clinical decision. ĭue to the rapid growth in sequencing throughput, cost reduction, improved sequencing chemistry, and the possibility to multiplex several sample/patients in a single sequencing experiment, Next Generation Sequencing (NGS) has become a powerful and efficient tool for disease causing variant identification and decoding of a number of genetically heterogeneous diseases including cancer. ClinQC is written in Python with multiprocessing capability, run on all major operating systems and is available at. ConclusionsĬlinQC is a powerful and easy to handle pipeline for quality control and trimming in clinical research. Our tool is expected to be very useful for quality control and format conversion of Sanger and NGS data to facilitate improved downstream analysis and mutation screening. It can analyze hundreds of sample/patients data in a single run and generate unified output files for both Sanger and NGS sequencing data. ClinQC output high quality reads in FASTQ format with Sanger quality encoding, which can be directly used in down-stream analysis. Next, it split bar-coded samples, filter duplicates, contamination and low quality sequences and generates a QC report. First, ClinQC convert input read files from their native formats to a common FASTQ format and remove adapters, and PCR primers. We have developed ClinQC, a flexible and user-friendly pipeline for format conversion, quality control, trimming and filtering of raw sequencing data generated from Sanger sequencing and three NGS sequencing platforms including Illumina, 454 and Ion Torrent. Therefore, integrated software tools are lacking which can analyze Sanger and NGS data together and eliminate platform specific sequencing errors, low quality reads and support the analysis of several sample/patients data set in a single run. However, in order to identify the potential disease causing mutations with great sensitivity and specificity it is essential to ensure high quality sequencing data. Therefore, for the efficient and affordable genetic testing, Next Generation Sequencing has been used as a complementary method with Sanger sequencing for disease causing mutation identification and confirmation in clinical research. With the advent of Next Generation Sequencing technologies, which produce data on unprecedented speed in a cost effective manner have overcome the limitation of Sanger sequencing. Traditional Sanger sequencing has been used as a gold standard method for genetic testing in clinic to perform single gene test, which has been a cumbersome and expensive method to test several genes in heterogeneous disease such as cancer.
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