Report
Evaluation of tools for differential gene expression analysis by RNA-seq on a 48 biological replicate experiment
| العنوان: | Evaluation of tools for differential gene expression analysis by RNA-seq on a 48 biological replicate experiment |
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| المؤلفون: | Schurch, Nicholas J., Schofield, Pieta, Gierliński, Marek, Cole, Christian, Sherstnev, Alexander, Singh, Vijender, Wrobel, Nicola, Gharbi, Karim, Simpson, Gordon G., Owen-Hughes, Tom, Blaxter, Mark, Barton, Geoffrey J. |
| سنة النشر: | 2015 |
| المجموعة: | Quantitative Biology |
| مصطلحات موضوعية: | Quantitative Biology - Genomics |
| الوصف: | An RNA-seq experiment with 48 biological replicates in each of 2 conditions was performed to determine the number of biological replicates ($n_r$) required, and to identify the most effective statistical analysis tools for identifying differential gene expression (DGE). When $n_r=3$, seven of the nine tools evaluated give true positive rates (TPR) of only 20 to 40 percent. For high fold-change genes ($|log_{2}(FC)|\gt2$) the TPR is $\gt85$ percent. Two tools performed poorly; over- or under-predicting the number of differentially expressed genes. Increasing replication gives a large increase in TPR when considering all DE genes but only a small increase for high fold-change genes. Achieving a TPR $\gt85$% across all fold-changes requires $n_r\gt20$. For future RNA-seq experiments these results suggest $n_r\gt6$, rising to $n_r\gt12$ when identifying DGE irrespective of fold-change is important. For $6 \lt n_r \lt 12$, superior TPR makes edgeR the leading tool tested. For $n_r \ge12$, minimizing false positives is more important and DESeq outperforms the other tools. Comment: 21 Pages and 4 Figures in main text. 9 Figures in Supplement attached to PDF. Revision to correct a minor error in the abstract |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1261/rna.053959.115 |
| URL الوصول: | http://arxiv.org/abs/1505.02017 |
| رقم الانضمام: | edsarx.1505.02017 |
| قاعدة البيانات: | arXiv |
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