exSeek: extracellular RNA analysis tool for noninvasive biomarker
The aim of this project is to combine small cell free RNA sequencing techniques with machine learning to identify promising candidate biomarker for cancers. We establish the pipeline from mapping to feature selection and propose a robust feature selection method to identify potential biomarkers.
Parts of this works difficulty is its steps and precision it requires. Since our exRNA-seq is different (it has less RNA reads), we have to explore the mapping sequence. We determine sequential mapping order, using peak calling because most long RNAs are fragments in blood. We also did matrix processing and robust feature selection for biomarker identification.
Work Summary
- work summary on 12.8:
- work summary on 10.10
We use our own data: HCC exRNA and two other data: exoRBase and GSE71008 to establish our robust feature selection methods.
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As teaching assistant of Bioinformatics Basics. I use part of our work to assign the final project of this semester’s course.