R Scripts for Microarray Analysis

           I  CCGG Methylome

           CEL intensities were quantile normalized, needs a  readcel.R function: normalization.txt

           SFP detection using enzyme-digested genomic DNA signals: sfp.txt

           A mixed effect model: intensity ~ genotype x enzyme /~plant (random effect) to analysis the constitutive CG methylation: parentallines.txt 

           A similar model: intensity ~ (additive + dominant + maternal) x enzyme /~plant (random effect) was used to analysis the constitutive and polymorphic CG methylation among 4 genotypes: mixedModel4lines2.txt 

           Genomic and genic distribution for constitutive and polymorphic CG methylation: parental.geno.dist.txt

           Correlation between constitutive CG methylation and absolute gene expression; correlation between CG methylation polymorphisms and gene expression polymorphisms: metylation.expr.txt

           Gene set enrichment: methyl.page.txt

           Comparison between CCGG methylome and ChIP-chip: fixing.txt 

            II  Transcriptome

            CEL files reading, spatial correction, quantile normalization, SFP and indel detection using genomic DNA signals: sfp.indel.txt

            CEL files reading, spatial correction, selection of probe sets, quantile normalization, and linear modeling for gene expression using mRNA signals: gene.expression.txt

            Linear modeling for exon expression using three approaches (correction by gene mean, correction by gene median and splicing index), and linear modeling for intron expression: splicing.txt

            Gene set enrichment for gene expression and exon/intron splicing: GO.txt

            HMM de novo transcript fragment detection, and comparison with annotation-based analysis: hmm.txt

            Genome browser: gbrowser.txt

            III Allele Specific Expression

          Working scripts…