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Empirical assessment of the impact of sample number and read depth on RNASeq analysis workflow performance

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RNA-Sequencing analysis methods are rapidly evolving, and the tool choice for each step of one common workflow, differential expression analysis, which includes read alignment, expression modeling, and differentially expressed gene identification, has a dramatic impact on performance characteristics. |

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International Project Risk Assessment: Methods, Procedures, and Critical Factors

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