A method of defining a selector set for a cancer comprising the steps of: (a) identifying genomic regions comprising mutations in one or more subjects from a population of subjects suffering from the cancer by; (i) selecting genes known to be drivers in the cancer of interest to generate a pool of known drivers; (b) ranking the genomic regions based on a Recurrence Index, wherein the RI of the genomic region is determined by dividing the number of subjects or tumors with mutations in the genomic region by the size of the genomic region; (ii) selecting exons from known drivers with the highest recurrence index that identify at least one new patient compared to step (a); and repeating until no further exons meet these criteria; (iii) identifying remaining exons of known drivers with an RI ≥ 30 and with SNVs covering ≥3 patients in the relevant database that result in the largest reduction in patients with only 1 SNV; and repeating until no further exons meet these criteria; (iv) repeating step (b) using RI ≥ 20; (v) adding in all exons from additional genes previously predicted to harbor driver mutations; and (vi) adding for known recurrent rearrangement the introns most frequently implicated in the fusion event and the flanking exons, wherein steps (i) - (vi) are embodied as a program of instructions executable by computer and performed by means of software components loaded into the computer; and (c) defining a selector set. (a) identifying genomic regions comprising mutations in one or more subjects from a population of subjects suffering from the cancer by; (i) selecting genes known to be drivers in the cancer of interest to generate a pool of known drivers; (i) selecting genes known to be drivers in the cancer of interest to generate a pool of known drivers; (b) ranking the genomic regions based on a Recurrence Index, wherein the RI of the genomic region is determined by dividing the number of subjects or tumors with mutations in the genomic region by the size of the genomic region; (ii) selecting exons from known drivers with the highest recurrence index that identify at least one new patient compared to step (a); and repeating until no further exons meet these criteria; (iii) identifying remaining exons of known drivers with an RI ≥ 30 and with SNVs covering ≥3 patients in the relevant database that result in the largest reduction in patients with only 1 SNV; and repeating until no further exons meet these criteria; (iv) repeating step (b) using RI ≥ 20; (v) adding in all exons from additional genes previously predicted to harbor driver mutations; and (vi) adding for known recurrent rearrangement the introns most frequently implicated in the fusion event and the flanking exons, wherein steps (i) - (vi) are embodied as a program of instructions executable by computer and performed by means of software components loaded into the computer; and (ii) selecting exons from known drivers with the highest recurrence index that identify at least one new patient compared to step (a); and repeating until no further exons meet these criteria; (iii) identifying remaining exons of known drivers with an RI ≥ 30 and with SNVs covering ≥3 patients in the relevant database that result in the largest reduction in patients with only 1 SNV; and repeating until no further exons meet these criteria; (iv) repeating step (b) using RI ≥ 20; (v) adding in all exons from additional genes previously predicted to harbor driver mutations; and (vi) adding for known recurrent rearrangement the introns most frequently implicated in the fusion event and the flanking exons, wherein steps (i) - (vi) are embodied as a program of instructions executable by computer and performed by means of software components loaded into the computer; (c) defining a selector set.