The Design Of Transcriptome Assembly Algorithm Based On Illumina Platform RNA Sequencing Datasets

With the development of sequencing technology,people know more about genome sequencing.Genome sequencing is to sequence genome segnent for species by using the sequencing platform,then assemble these sequencing segments accurately to get the complete genome sequence information to analyze the genome's sequence and predict the function.As an important problem of genome sequencing,transcriptome assembly is to assemble species' RNA reads by some algorithms to get their complete sequence information.The research of transcriptome's reads assembly plays an important role in the construction of human's complete transcriptome and the prediction of human's disease related to heredity and variation.Transcriptome assembly algorithm can be divided into two categories,which is respectively genome-guided and de novo transcriptome assembly algorithm.Because genome-guided algorithm requires species' complete sequencing genome sequence,the applicability of this method is not so wide.In order to apply to the species lack of reference genome,an algorithm named SS-Assembler is designed in this paper.The datasets we use in this paper is the high throughput next generation RNA sequencing data from the most popular company,Illumina,and we use double hash table to save data.The programming language we use is Python.The innovation of the algorithm is that we abandon traditional De Bruijn graph but use double hash table to save k-mer?which help save a lot of running time and improve the accuracy of algorithm.When tested,the algorithm we design performs better than existed transcriptome assembly algorithms in accuracy and time complexity,which is of great academic value in promoting the solution of transcriptome assembly problem.