RASflow: An RNA-Seq Analysis Workflow with Snakemake

Abstract

Background: With the cost of DNA sequencing decreasing, increasing amounts of RNA-Seq data are being generated giving novel insight into gene expression and regulation. Prior to analysis of gene expression, the RNA-Seq data has to be processed through a number of steps resulting in a quantification of expression of each gene / transcript in each of the analyzed samples. A number of workflows are available to help researchers perform these steps on their own data, or on public data to take advantage of novel software or reference data in data re-analysis. However, many of the existing workflows are limited to specific types of studies. We therefore aimed to develop a maximally general workflow, applicable to a wide range of data and analysis approaches and at the same time support research on both model and non-model organisms. Furthermore, we aimed to make the workflow usable also for users with limited programming skills.Results: Utilizing the workflow management system Snakemake and the package management system Conda, we have developed a modular, flexible and user-friendly RNA-Seq analysis pipeline: RNA-Seq Analysis Snakemake Workflow (RASflow). Utilizing Snakemake and Conda alleviates challenges with library dependencies and version conflicts and also supports reproducibility. To be applicable for a wide variety of applications, RASflow supports mapping of reads to both genomic and transcriptomic assemblies. RASflow has a broad range of potential users: it can be applied by researchers interested in any organism and since it requires no programming skills, it can be used by researchers with different backgrounds. RASflow is an open source tool and source code as well as documentation, tutorials and example data sets can be found on GitHub: https://github.com/zhxiaokang/RASflow Conclusions: RASflow is a simple and reliable RNA-Seq analysis workflow which is a full pack of RNA-Seq analysis.

RNAflow: An Effective and Simple RNA-Seq Differential Gene Expression Pipeline Using Nextflow

“…Both pipelines provide true encapsulated containerization, also for the operating system, to minimize effects of numerical instability. [ 4 ] and [ 50 ] make use of Snakemake [ 51 ], another popular bioinformatic workflow management tool. Thus, it is easy to parallelize and use Conda in order to install all of its dependencies.…”

“…✓—feature available/supported; ✗—feature not available/supported; ✱—feature partially supported. RNAflow VIPER [ 4 ] Nextpresso [ 5 ] TRAPLINE [ 6 ] RNAsik [ 7 ] hppRNA [ 8 ] nf-core/rnaseq [ 9 ] RCP [ 10 ] RASflow [ 50 ] OneStopRNAseq [ 53 ] Pipeline scope Read QC ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Trimming ✓ ✗ ✓ ✓ ✗ ✓ ✓ ✓ ✓ ✗ rRNA removal ✓ ✱ no automatic removal ✗ ✗ ✗ ...…”

The chemical defensome of five model teleost fish

“…For stickleback, embryos were sampled at early morula, late morula, mid-gastrula, early organogenesis, and 24 h post hatching (hph). The sequencing data was processed and analyzed following the automatic pipeline RASflow 27 . Briefly, the reads were mapped to the stickleback genome downloaded from ENSEMBL of version release-100.…”

Appyters: Turning Jupyter Notebooks into data-driven web apps

“…We and others developed several RNA-seq data analysis pipelines that cover many of these steps. [26][27][28][29][30] The Bulk RNA-Seq Analysis Appyter enables non-computational users to analyze and visualize their own RNA-seq datasets with an array of downstream analysis and visualization tools. The Appyter starts with an expression matrix of raw read counts and a file that provides metadata describing each sample.…”