Notes, Costanzo SGA 2010

Costanzo et al 2010, SGA genetic interaction dataset

Costanzo10 model double mutant colony size (growth fitness)  as $C_ij = f_ij * t * s_ij * e$.

The double mutant fitness $f_ij = f_i * f_j + epsilon$.  Hence, 

So, for perfect synthetical lethals $f_ij$=0,  and $f_i= f_j= 1$, we should have $epsilon = -1$.
Costanzo10 defines negative interaction as $epsilon<0, and positive interaction as $epsilon>0$. Because the measure is based on loss of function assay, the actual function of the wildtype genes are just opposite.

Extreme examples of negative interactions are synthetic lethality. Positive interactions may indicate antagonizing activities (Thanks to my friends for pointing this out).

It is interesting that Costanzo10 recovered only 30% of the published synthetic lethality. It is possible growth defect of most single deletion mutant in synthetic lethal pairs is often de-emphasized.


The SGA genetic interaction dataset is available for download in various text formats
(see Data Files S1-S5) or through a web-based database, DRYGIN (http://drygin.ccbr.utoronto.ca, (S2)). SGA data can also be explored through the SGAExpress browser (http://www.ailab.si/sgaexpress).

For stringent cutoff, epsilon < -0.12 with p<0.05 and epsilon > 0.16 with p < 0.05.


#genetic network in pairs
GIN.pairs.tb = read.csv("sgadata_costanzo2009_stringentCutoff_101120.csv", header=F,
                        colClass=c("character","character","character","character",NA,NA,NA))
names(GIN.pairs.tb) = c("ORF1", "name1", "ORF2", "name2", "epsilon", "stddev", "p")
#epsilon = fij - fi * fj
PositiveGIN.pairs.tb = GIN.pairs.tb[GIN.pairs.tb$epsilon>0, ]
NegativeGIN.pairs.tb = GIN.pairs.tb[GIN.pairs.tb$epsilon<0, ]
str(PositiveGIN.pairs.tb)
str(NegativeGIN.pairs.tb)