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      Pipeliner: A Nextflow-Based Framework for the Definition of Sequencing Data Processing Pipelines

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          Abstract

          The advent of high-throughput sequencing technologies has led to the need for flexible and user-friendly data preprocessing platforms. The Pipeliner framework provides an out-of-the-box solution for processing various types of sequencing data. It combines the Nextflow scripting language and Anaconda package manager to generate modular computational workflows. We have used Pipeliner to create several pipelines for sequencing data processing including bulk RNA-sequencing (RNA-seq), single-cell RNA-seq, as well as digital gene expression data. This report highlights the design methodology behind Pipeliner that enables the development of highly flexible and reproducible pipelines that are easy to extend and maintain on multiple computing environments. We also provide a quick start user guide demonstrating how to setup and execute available pipelines with toy datasets.

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          Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences

          Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy http://usegalaxy.org, an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis.
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            Alternative preprocessing of RNA-Sequencing data in The Cancer Genome Atlas leads to improved analysis results.

            The Cancer Genome Atlas (TCGA) RNA-Sequencing data are used widely for research. TCGA provides 'Level 3' data, which have been processed using a pipeline specific to that resource. However, we have found using experimentally derived data that this pipeline produces gene-expression values that vary considerably across biological replicates. In addition, some RNA-Sequencing analysis tools require integer-based read counts, which are not provided with the Level 3 data. As an alternative, we have reprocessed the data for 9264 tumor and 741 normal samples across 24 cancer types using the Rsubread package. We have also collated corresponding clinical data for these samples. We provide these data as a community resource.
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              How leaders influence the impact of affective events on team climate and performance in R&D teams

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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                28 June 2019
                2019
                : 10
                : 614
                Affiliations
                [1] 1Bioinformatics Program, Boston University , Boston, MA, United States
                [2] 2Division of Computational Biomedicine, Boston University School of Medicine , Boston, MA, United States
                Author notes

                Edited by: Vinicius Maracaja-Coutinho, Universidad de Chile, Chile

                Reviewed by: Pao-Yang Chen, Academia Sinica, Taiwan; Ernesto Picardi, University of Bari Aldo Moro, Italy

                *Correspondence: Anthony Federico, anfed@ 123456bu.edu ; Stefano Monti, smonti@ 123456BU.EDU

                This article was submitted to Bioinformatics and Computational Biology, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2019.00614
                6609566
                31316552
                dbc75273-c359-483d-825a-c9cf145eaed4
                Copyright © 2019 Federico, Karagiannis, Karri, Kishore, Koga, Campbell and Monti

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 21 November 2018
                : 13 June 2019
                Page count
                Figures: 6, Tables: 1, Equations: 0, References: 16, Pages: 7, Words: 2755
                Categories
                Genetics
                Technology Report

                Genetics
                pipeline development,sequencing workflows,nextflow,rna-seq pipeline,scrna-seq pipeline
                Genetics
                pipeline development, sequencing workflows, nextflow, rna-seq pipeline, scrna-seq pipeline

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