A method for sequence analysis, comprising: (a) obtaining multiple pairs of primers that are compatible in a multiplex PCR reaction; (b) setting up at least two multiplex PCR reactions each containing different portions of the same sample, wherein at least some of the primer pairs are in more than one PCR reaction and at least one of the PCR reactions contains some but not all of the primer pairs of the other reaction(s); (c) thermocycling the multiplex PCR reactions to produce multiple replicate amplicons; (d) sequencing the amplicons to produce sequence reads; (e) computationally analyzing the sequence reads from replicate amplicons for a selected sequence variation to produce a score for the selected sequence variation, wherein the score: i. is based on the number of replicate amplicons that comprise a sequence variation that has a frequency above a cut-off, wherein the cut-off establishes a baseline for identifying variations that are statistically unlikely to be background; or ii. indicates the strength of the combined evidence for the sequence variation across the replicates, wherein the combined evidence for the sequence variation is summarized using a likelihood value or using Bayesian statistics; (f) calling the sequence variation as a genetic variation based on the score by comparing the score to a threshold at or above which a genetic variation can be called, wherein when the score is produced according to e)ii), the threshold is a likelihood threshold or is a Bayes factor that can be altered by prior distributions, wherein the sample is obtained from a biological sample from a patient. (a) obtaining multiple pairs of primers that are compatible in a multiplex PCR reaction; (b) setting up at least two multiplex PCR reactions each containing different portions of the same sample, wherein at least some of the primer pairs are in more than one PCR reaction and at least one of the PCR reactions contains some but not all of the primer pairs of the other reaction(s); (c) thermocycling the multiplex PCR reactions to produce multiple replicate amplicons; (d) sequencing the amplicons to produce sequence reads; (e) computationally analyzing the sequence reads from replicate amplicons for a selected sequence variation to produce a score for the selected sequence variation, wherein the score: i. is based on the number of replicate amplicons that comprise a sequence variation that has a frequency above a cut-off, wherein the cut-off establishes a baseline for identifying variations that are statistically unlikely to be background; or ii. indicates the strength of the combined evidence for the sequence variation across the replicates, wherein the combined evidence for the sequence variation is summarized using a likelihood value or using Bayesian statistics; i. is based on the number of replicate amplicons that comprise a sequence variation that has a frequency above a cut-off, wherein the cut-off establishes a baseline for identifying variations that are statistically unlikely to be background; or ii. indicates the strength of the combined evidence for the sequence variation across the replicates, wherein the combined evidence for the sequence variation is summarized using a likelihood value or using Bayesian statistics; (f) calling the sequence variation as a genetic variation based on the score by comparing the score to a threshold at or above which a genetic variation can be called, wherein when the score is produced according to e)ii), the threshold is a likelihood threshold or is a Bayes factor that can be altered by prior distributions, <EOS>