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|title= Assessing the size of gene or RNAi effects in multifactor high-throughput experiments
|journal=Pharmacogenomics |volume=11 |issue= |pages=199–213
|year=2010 |month= |pmid= 20136359|doi=10.2217/PGS.09.136 |url=}}</ref> The commonly used dual-flashlight plot is for the difference between two groups in high-throughput experiments such as [[microarray]]s and [[high-throughput screening]] studies, in which we plot the [[SSMD]] versus average log fold-change on the ''y''- and ''x''-axes, respectively, for all genes or compounds (such as [[siRNA]]s or [[small molecule]]s) investigated in an experiment.<ref name="ZhangPharmacogenomics2010"/>
As a whole, the points in a dual-flashlight plot look like the beams of a flashlight with two heads, hence the name dual-flashlight plot.<ref name="ZhangPharmacogenomics2010"/>
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.<ref name=Cui2003>{{cite journal |author= Cui X, Churchill GA
|title=Statistical tests for differential expression in cDNA microarray experiments
|journal= Genome Biology |volume=4 |issue= 4|pages=210
|year=2003 |month= |pmid=1270220 |doi= |url=}}</ref> The advantage of using SMCV over [[p-value]] (or [[q-value]]) is that, if there exist any non-zero true effects for a gene or compound, the estimated SMCV goes to its population value whereas the [[p-value]] (or [[q-value]]) for testing no mean difference (or zero contrast mean) goes to zero when the sample size increases
.<ref name=ZhangSBR2010>{{cite journal |author=Zhang XHD
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