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EDDA can aid in the design of a range of common experiments such as RNA-seq, Nanostring assays, RIP-seq and Metagenomic sequencing, and enables researchers to comprehensively investigate the impact of experimental decisions on the ability to detect differential abundance. This work was published on 3 December 2014 at Genome Biology under the title "The importance of study design for detecting differentially abundant features in high-throughput experiments" (http://genomebiology.com/2014/15/12/527).
Package details |
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Author | Li Juntao, Luo Huaien, Chia Kuan Hui Burton, Niranjan Nagarajan |
Bioconductor views | ChIPSeq ExperimentalDesign ImmunoOncology Normalization RNASeq Sequencing |
Maintainer | Chia Kuan Hui Burton <chiakhb@gis.a-star.edu.sg>, Niranjan Nagarajan <nagarajann@gis.a-star.edu.sg> |
License | GPL (>= 2) |
Version | 1.28.0 |
URL | http://edda.gis.a-star.edu.sg/ http://genomebiology.com/2014/15/12/527 |
Package repository | View on Bioconductor |
Installation |
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