Quality control method based on pacbio full-length transcriptome sequencing data

Abstract

The present invention provides a quality control method based on PacBio full-length transcriptome sequencing data, including steps: 1) using the IsoSeq analysis process to obtain high-quality and low-quality consistent full-length sequences from the original PacBio full-length transcriptome sequencing data; 2) Correct low-quality consensus full-length sequences based on Illumina sequencing data, and filter sequences that still fail to meet high-quality standards; 3) Merge high-quality and low-quality consistent full-length sequences that meet the conditions after correction, and filter according to the following criteria : Remove overly long sequences generated by sequence chimerism; remove consensus full-length sequences that have palindromic sequences in their own alignment results; remove sequences that can be aligned to multiple positions by other consistent full-length sequences. The chimeric sequences that may exist in the consensus full-length sequence are filtered through multiple criteria, reducing the proportion of false positive results in the final transcriptome and improving the accuracy of subsequent transcriptome-related analysis results.

Description

technical field [0001] The invention relates to the technical field of bioinformatics, in particular to a quality control method based on PacBio full-length transcriptome sequencing data, which is used for filtering chimeric sequences in the PacBio full-length transcriptome sequencing data. Background technique [0002] The transcriptome is the link between the genetic information of the genome and the proteome of biological functions. The regulation of the transcription level is the most important and the most widely studied method of organism regulation. Transcriptome research is one of the essential tools for understanding life processes. Transcriptome sequencing can sequence the transcriptome of a sample at any time point or under any condition, dynamically reflect the gene transcription level, simultaneously identify and quantify rare transcripts and normal transcripts, and provide sample-specific transcript sequence structure information. [0003] However, sequencing t...

AI Technical Summary

Problems solved by technology

In the full-length sequence recognition step, filter out some chimeric sequences by judging whether there is a primer sequence in the middle of the sequence (see figure 1 ), but there are still some chimeric sequences that have not been filtered due to the inability to correctly identify the primer sequence

Especially in the absence of a sequenced species reference genome, it is not possible to identify possible chimeric sequences through alignment information with the reference genome

These unrecognized chimeric sequences are retained in the final transcriptome, which will have a great impact on the accuracy of subsequent transcriptome-related analysis results

In order to improve the accuracy of transcriptome sequencing data, it is necessary to further remove the chimeric sequences that cannot be identified in the prior art, but there is no relevant method reported so far

Images