Dual-flashlight plot: Difference between revisions

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{{Expert-subject needed|Statistics|date=August 2011}}
[[Image:wiki.dualflashlight.png|thumb|350px|Dual-flashlight plot showing a high-throughput screening dataset.]]
 
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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"/>
 
With the dual-flashlight plot, we can see how the genes or compounds are distributed into each category in effect sizes, as shown in the figure. Meanwhile, we can also see the average fold-change for each gene or compound. The dual-flashlight plot is similar to the [[volcano plot (statistics)|volcano plot]]. In a [[volcano plot (statistics)|volcano plot]], the [[p-value]] (or q-value{{clarify|date=June 2012}}), instead of SMCV or SSMD, is plotted against average fold-change <ref name=Jin2001>{{cite journal |authorvauthors=Jin W, Riley RM, Wolfinger RD, White KP, Passador-Gurgel G, Gibson G |title= The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster
|title= The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster
|journal= Nature Genetics |volume=29 |issue= |pages=389–95
|year=2001 |month= |pmid= |doi= 10.1038/ng766 |url=}}</ref>
.<ref name=Cui2003>{{cite journal |authorvauthors= Cui X, Churchill GA |title=Statistical tests for differential expression in cDNA microarray experiments
|title=Statistical tests for differential expression in cDNA microarray experiments
|journal= Genome Biology |volume=4 |issue= 4|pages=210
|year=2003 |month= |pmid=12702200 |doi= 10.1186/gb-2003-4-4-210|url= |pmc=154570}}</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