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Ready Solutions Engineering Test Results

RNA-Seq pipeline benchmark with Dell EMC Ready

Bundle for HPC Life Sciences

Deferentially Expressed Gene (DEG) Analysis with Tuxedo Pipeline

Overview

Gene expression analysis is as important as identifying Single Nucleotide Polymorphism, indel or chromosomal restructuring.

Eventually, the entire physiological and biochemical events depend on the final gene expression products, proteins. Many quantitative

scientists, non-biologists tend to oversimplify the flow of genetic information and forget about what the actual roles of proteins are.

Simplification is the beginning of most science fields; however, it is too optimistic to think that this practice also works for biology.

Although all the human organs contain the identical genomic composition, the actual protein expressed in various organs are

completely different. Ideally, a technology enables to quantify the entire proteins in a cell could excel the progress of Life Science

significantly; however, we are far from to achieving it. Here, in this blog, we test one popular RNA-Seq data analysis pipeline known as

Tuxedo pipeline. The Tuxedo suite offers a set of tools for analyzing a variety of RNA-Seq data, including short-read mapping,

identification of splice junctions, transcript and isoform detection, differential expression, visualizations, and quality control metrics.

A typical RNA-Seq data set consists of multiple samples as shown in Figure 1. Although the number of sample sets depends on the

biological experimental designs, two sets of samples are used to make comparisons between normal vs. cancer samples or untreated

vs. treated samples, for examples.

Figure 1 Tested Tuxedo pipeline workflow

Summary of content (6 pages)

PAGE 1
Ready Solutions Engineering Test Results 1 RNA-Seq pipeline benchmark with Dell EMC Ready Bundle for HPC Life Sciences Deferentially Expressed Gene (DEG) Analysis with Tuxedo Pipeline Overview Gene expression analysis is as important as identifying Single Nucleotide Polymorphism, indel or chromosomal restructuring. Eventually, the entire physiological and biochemical events depend on the final gene expression products, proteins.
PAGE 2
Ready Specs 2 All the samples are aligned individually in Step 1. In this pipeline, the Tophat process uses Bowtie 2 version 2.3.1 as an underlying short sequence read aligner. Step 3, Cuffmerge job has a dependency from all the previous jobs in Step 2. The results from Cufflinks jobs are collected at this step to merge together multiple Cufflinks assemblies which is required for Cuffdiff step. Cuffmerge also runs Cuffcompare in the background and automatically filters out transcription artifacts.
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Ready Specs 3 Performance Evaluation Two sample Test – Bare-minimum DEG analysis requires at least two samples. In Figure 2, each step described in Figure 1 is submitted to Slurm job scheduler with proper dependencies. For example, Cuffmerge step must wait for all the Cufflinks jobs are completed. Two samples, let’s imagine one normal and one treated sample, begin with Tophat step individually and followed by Cufflinks step.
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Ready Specs 4 Figure 3 Volcano plot of the Cuffdiff results Throughput Test – Single pipeline with more than two samples - Biological / Technical replicates Typical RNA-Seq studies consist of multiple samples, sometime 100s of different samples, normal versus disease or untreated versus treated samples. These samples tend to have high level of noisy due to their biological reasons; hence, the analysis requires vigorous data preprocessing procedure.
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Ready Specs 5 Figure 4 Runtime and throughput results Figure 5 Behaviors of Cuffmerge, Cuffdiff and Cuffnorm
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Ready Specs 6 Conclusion The throughput test results show that 8 node PowerEdge C6420s with Isilon H600 can process roughly 1 Billion Fragments which is little more than 32 samples with ~50 million paired reads each (25 MF) through Tuxedo pipeline illustrated in Figure 1. Since Tuxedo pipeline is relatively faster than other popular pipelines, it is hard to generalize or utilize these results for sizing a HPC system. However, this provides a good reference point to help designing a right size HPC system.