Method of estimating transcript abundances comprising the steps of a) obtaining transcript fragment sequencing data from a potential mixture of transcripts of a genetic locus of interest, b) assigning said fragment sequencing data to genetic coordinates of said locus of interest thereby obtaining a data set of fragment genetic coordinate coverage, said coverage for each genetic coordinate combined forming a coverage envelope curve, c) setting a number of transcripts of said mixture, wherein pre-annotated sequence data from the genetic locus of interest is obtained and the number of transcripts is set to at least the number of different isoforms, including splice variants counting as different isoforms, expected from said genetic locus of interest, d) pre-setting a probability distribution function of modelled genetic coverage for each transcript i, with i denoting the numerical identifier for a transcript, wherein said probability distribution function is defined by a weight factor α i of said transcript i multiplied with the sum of at least 2 probability subfunctions j, with j denoting the numerical identifier for a probability subfunction, each probability subfunction j being independently weighted by a weight factor β i,j, wherein the probability subfunctions j are aperiodic functions, wherein the probability subfunctions j for a transcript are positioned or shifted in the genetic coordinate to cover the entire length of a transcript with a positive value, e) adding the probability distribution functions of each transcript to obtain a sum function, f) fitting the sum function to the coverage envelope curve thereby optimizing the values for α i and β i,j to increase the fit, g) repeating steps e) and f) until a pre-set convergence criterion has been fulfilled, thereby obtaining the estimated transcript abundance for each transcript of the mixture given by the weight factor α i as optimized after the convergence criterion has been fulfilled; wherein steps b)-g) are computer-implemented. a) obtaining transcript fragment sequencing data from a potential mixture of transcripts of a genetic locus of interest, b) assigning said fragment sequencing data to genetic coordinates of said locus of interest thereby obtaining a data set of fragment genetic coordinate coverage, said coverage for each genetic coordinate combined forming a coverage envelope curve, c) setting a number of transcripts of said mixture, wherein pre-annotated sequence data from the genetic locus of interest is obtained and the number of transcripts is set to at least the number of different isoforms, including splice variants counting as different isoforms, expected from said genetic locus of interest, d) pre-setting a probability distribution function of modelled genetic coverage for each transcript i, with i denoting the numerical identifier for a transcript, wherein said probability distribution function is defined by a weight factor α i of said transcript i multiplied with the sum of at least 2 probability subfunctions j, with j denoting the numerical identifier for a probability subfunction, each probability subfunction j being independently weighted by a weight factor β i,j, wherein the probability subfunctions j are aperiodic functions, wherein the probability subfunctions j for a transcript are positioned or shifted in the genetic coordinate to cover the entire length of a transcript with a positive value, e) adding the probability distribution functions of each transcript to obtain a sum function, f) fitting the sum function to the coverage envelope curve thereby optimizing the values for α i and β i,j to increase the fit, g) repeating steps e) and f) until a pre-set convergence criterion has been fulfilled, thereby obtaining the estimated transcript abundance for each transcript of the mixture given by the weight factor α i as optimized after the convergence criterion has been fulfilled;