Gene Set Analysis Using Spatial Statistics
نویسندگان
چکیده
Gene differential expression consists of the study possible association between gene expression, evaluated using different types data as DNA microarray or RNA-Seq technologies, and phenotype. This can be performed marginally for each (differential expression) a set collection (gene analysis). A previous (marginal) per-gene analysis is usually in order to obtain significant genes marginal p-values used later phenotype expression. paper proposes use methods spatial statistics testing paired samples counts. approach not based on analysis. Instead, we compare counts within sample/control binomial test. Each pair per will produce p-value so profile transformed into vector which considered an event belonging point pattern. would first component bivariate The second generated by applying two randomization distributions correspondence treatment. self-contained null hypothesis formulated terms associated pattern random labeling sets were defined Ontology (GO) Kyoto Encyclopedia Genes Genomes (KEGG) pathways. proposed methodology was tested four datasets colorectal cancer (CRC) patients results contrasted with those obtained edgeR-GOseq pipeline. has proved consistent at biological statistical level, particular Cuzick Edwards test one realization between-pair distribution.
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ژورنال
عنوان ژورنال: Mathematics
سال: 2021
ISSN: ['2227-7390']
DOI: https://doi.org/10.3390/math9050521