Abstract
BackgroundsNext-Generation Sequencing (NGS) is now widely used in biomedical research for various applications. Processing of NGS data requires multiple programs and customization of the processing pipelines according to the data platforms. However, rapid progress of the NGS applications and processing methods urgently require prompt update of the pipelines. Recent clinical applications of NGS technology such as cell-free DNA, cancer panel, or exosomal RNA sequencing data also require appropriate customization of the processing pipelines. Here, we developed SEQprocess, a highly extendable framework that can provide standard as well as customized pipelines for NGS data processing.ResultsSEQprocess was implemented in an R package with fully modularized steps for data processing that can be easily customized. Currently, six pre-customized pipelines are provided that can be easily executed by non-experts such as biomedical scientists, including the National Cancer Institute’s (NCI) Genomic Data Commons (GDC) pipelines as well as the popularly used pipelines for variant calling (e.g., GATK) and estimation of allele frequency, RNA abundance (e.g., TopHat2/Cufflink), or DNA copy numbers (e.g., Sequenza). In addition, optimized pipelines for the clinical sequencing from cell-free DNA or miR-Seq are also provided. The processed data were transformed into R package-compatible data type ‘ExpressionSet’ or ‘SummarizedExperiment’, which could facilitate subsequent data analysis within R environment. Finally, an automated report summarizing the processing steps are also provided to ensure reproducibility of the NGS data analysis.ConclusionSEQprocess provides a highly extendable and R compatible framework that can manage customized and reproducible pipelines for handling multiple legacy NGS processing tools.
Highlights
Six pre-customized pipelines are provided that can be executed by nonexperts such as biomedical scientists, including the National Cancer Institute’s (NCI) Genomic Data Commons (GDC) pipelines as well as the popularly used pipelines for variant calling (e.g., GATK) and estimation of allele frequency, RNA abundance (e.g., TopHat2/Cufflink), or DNA copy numbers (e.g., Sequenza)
Next-Generation Sequencing (NGS) technology is widely used in biomedical research fields, and is extensively being used in the clinic [9]
We developed a SEQprocess that provides fully customizable NGS processing pipelines covering the GDC pipelines and new data for clinical applications
Summary
The current version of SEQprocess provided six different pre-customized standard pipelines, including the pipelines for GDC processing and the newly adapted clinical applications for cell-free DNAs (cfDNA) or exosomal miRNAs (Fig. 1) These pipelines ran by a one-step command that could be executed by non-expert users. Values File path File path File path Name WGS, WES, BarSEQ, RSEQ, miRSEQ none, GDC, GATK, BarSEQ, Tuxedo, miRSEQ Numeric Logical Logical trim.galore, cutadapt, none bwa, tophat, star, bowtie, none Logical Numeric mem, aln Numeric Numeric MarkDuplicates, BARCODE, none Logical gatk, varscan, mutect, muse, somaticsniper, none Numeric Numeric annovar, vep Default = hg cufflinks, htseq, none -G, −g Numeric mRNA, miRNA Logical Logical Logical Logical. Multi-threading support in each program of GATK, TopHat, BWA, STAR, and Cufflinks could be controlled by the program arguments Each step of these pipelines are modularized as a wrapper function in R package to provide an easy customization platform. We have provided an example data (‘inst/example’) and a script (‘example/example.R’)
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