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. 2022 Aug 9;2(6):894–902. doi: 10.1016/j.fmre.2022.07.011

Table 1.

Overview of analysis methods for molecular biomarkers.

Methods Description Applications Reference
DESeq2 A method using shrinkage estimation for differential expression analysis of count data. Quantitative analysis of comparative RNA-seq data using shrinkage estimators for dispersion and fold change. [13]
edgeR Examining differential expression of replicated count data. Can be used
in experiments that generate counts.
[14]
SVM A powerful method to build a classifier. Cancer genomic classification or subtyping. [15, 16]
PLS-DA A discrimination method based on PLS regression. Predictive and descriptive modeling as well as for discriminative variable selection. [17], [18], [19]
LASSO A shrinkage and selection method for linear regression. Estimating parameters and selecting variables. [20]
RFE Method of gene selection utilizing SVM methods based on recursive feature elimination. Selecting features by recursively considering smaller sets of features. [21]