Backgrounds: Next-Generation Sequencing (NGS) is now widely used in biomedical research for various\napplications. Processing of NGS data requires multiple programs and customization of the processing pipelines\naccording to the data platforms. However, rapid progress of the NGS applications and processing methods urgently\nrequire prompt update of the pipelines. Recent clinical applications of NGS technology such as cell-free DNA,\ncancer panel, or exosomal RNA sequencing data also require appropriate customization of the processing pipelines.\nHere, we developed SEQprocess, a highly extendable framework that can provide standard as well as customized\npipelines for NGS data processing.\nResults: SEQprocess was implemented in an R package with fully modularized steps for data processing that can\nbe easily customized. Currently, six pre-customized pipelines are provided that can be easily executed by nonexperts\nsuch as biomedical scientists, including the National Cancer Instituteâ??s (NCI) Genomic Data Commons (GDC)\npipelines as well as the popularly used pipelines for variant calling (e.g., GATK) and estimation of allele frequency,\nRNA abundance (e.g., TopHat2/Cufflink), or DNA copy numbers (e.g., Sequenza). In addition, optimized pipelines for\nthe clinical sequencing from cell-free DNA or miR-Seq are also provided. The processed data were transformed into\nR package-compatible data type â??ExpressionSetâ?? or â??SummarizedExperimentâ??, which could facilitate subsequent data\nanalysis within R environment. Finally, an automated report summarizing the processing steps are also provided to\nensure reproducibility of the NGS data analysis.\nConclusion: SEQprocess provides a highly extendable and R compatible framework that can manage customized\nand reproducible pipelines for handling multiple legacy NGS processing tools.
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