Diagnosis of thyroid neoplasm using support vector machine algorithms based on platelet RNA-seq.

ABSTRACT:

Objective

To assess the capacity of support vector machine (SVM) algorithms that are developed based on platelet RNA-seq data in identifying thyroid neoplasm patients and differentiating patients with thyroid adenomas, papillary thyroid cancer and metastasized papillary thyroid cancer.

Methods

Platelets were collected and isolated from 109 patients and 63 healthy controls. RNA-seq was performed to find transcripts with differential levels. Genes corresponding to these altered transcripts were identified using R packages. All samples were subsampled into a training set and a validation set. Two SVM algorithms were developed and trained with the training set, using the genes with differential transcript levels (GDTLs) as classifiers, and validated with the validation set. GO a

SUBMITTER: Shen Y 

PROVIDER: S-EPMC8159845 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature