Predictive analysis method, device, equipment and medium for lncRNA target gene

Abstract

The invention provides a predictive analysis method, device and equipment for an lncRNA target gene and a medium. The method comprises the following steps: counting the sum of repeated mRNA expressionquantities in each treatment, and filtering mRNA sequences of which the sum of the expression quantities is zero according to the expression quantities; carrying out correlation analysis on the expression quantities of the mRNA and the lncRNA, extracting a corresponding correlation coefficient and a probability P value as a correlation judgment standard to merge and remove redundancy, and respectively storing in an mRNA file and an lncRNA file; splitting the lncRNA sequence after redundancy removal according to a specified sequence number to generate batch task running shell scripts respectively, and submitting the batch task running shell scripts to a cluster to realize multi-thread running. According to the method, the number of the target genes to be predicted of the lncRNA is reduced,the prediction false positive rate of the lncRNA target genes is reduced, and the prediction efficiency of the lncRNA target genes is optimized and improved from the aspects of false positive removaland multithreading.

Description

technical field [0001] The invention relates to the technical field of gene prediction, in particular to a method, device, equipment and medium for predicting and analyzing lncRNA target genes. Background technique [0002] lncRNA is a long-chain non-coding RNA sequence with a sequence length greater than 200bp, which binds to DNA and transcription and translation intermediates in the form of RNA, and then participates in the regulation of transcription interference, transcription activation, protein expression and other important biological processes. Existing studies have not found any important findings on the exploration of lncRNA regulation mode. Therefore, the prediction of lncRNA target genes is currently the key to the functional research of lncRNA. [0003] The prediction method is to anchor the specific mRNA of the predicted lncRNA sequence as the target gene of the lncRNA, and then qualitatively annotate the lncRNA function through the function of the target gene...

AI Technical Summary

Problems solved by technology

[0005] However, the sequence similarity analysis is based on the calculation of energy values, which requires a comparison of the similarity between sequences, which requires a lot of calculations.

At present, the prediction speed of existing lncRNA prediction software based on energy value is relatively slow, and the prediction time increases linearly with the number of sequences. According to recent research results, the improvement of lncRNA prediction speed based on algorithm optimization has reached a bottleneck state. Trans target gene prediction is based on The prediction speed of the algorithm for evaluating sequence similarity is slow, which limits the prediction efficiency; in addition, the accuracy of prediction analysis based on expression correlation is relatively reduced

Only statistically, the correlation analysis of the expression levels of two genes is prone to false positives in genes with lower expression levels

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