In the field of network theory, the so called \u201cexplosive percolation\u201d phenomenon has recently raised great interest, in which a giant cluster transition is obtained by the addition of a negligibly small number of links (as opposed to erdos-renyi classical random networks). We describe a similar behaviour in networks obtained from a correlation matrix of randomly generated vectors, both in the limit of high correlation and anti-correlation. This phenomenon is relevant in many practical applications, from financial to high-throughput genomic data analysis, in which time correlation is widely applied to characterize the global and local dynamics of the system
