Using RaMWAS with Illumina HumanMethylation450K or MethylationEPIC arrays | Required packages | Download example (public) data | Loading IDAT files | Probe and sample level quality control | Probes with SNPs and in cross-reactive regions | Probes with low bead count | Probes and samples with low detection p-values | Exclusion of low quality samples and probes | Obtain methylation estimates and save in RaMWAS format | Covariates for analysis | Principal components analysis (PCA) on control probes | Cell type composition | Median methylated and unmethylated intensity | Phenotypic covariates from the sample sheet | Running RaMWAS on the data | Set up parameters and covariates | Covariate pruning | MWAS without covariates (high inflation factor) | MWAS with all covariates (moderate inflation factor) | Further steps of RaMWAS pipeline

Using RaMWAS with other methylation platforms or data types | Import data from other sources | Principal Component Analysis (PCA) | PCA with batch regressed out | Association testing | Further steps of RaMWAS pipeline | Cleanup | Version information

Introduction | Getting started | Installation | Loading package and viewing documentation | RaMWAS steps | Scan BAM files and calculate QC indices | Summarize QC measures | Calculate CpG score matrix | Principal component analysis | Methylome-wide association study (MWAS) | Annotation of top results | Methylation risk score | CpG-SNP analysis | Directory names | Version information | References

Downloadable CpG sets | Constructing a custom CpG set | Constructing a CpG set for a reference genome | In silico alignment experiment

Initializing RaMWAS parameters | Explanation of all parameters | Parameters pointing to directories | Parameters pointing to files | BAM names | BAM to sample matching | CpG locations | File with covariates | Multithreading | Read filtering | Coverage matrix | PCA and MWAS | Annotation of top findings | Methylation risk score | Choosing the number of folds cvnfolds in the cross validation | Joint analysis with genotype data

Introduction | Creating a filematrix | Reading from and writing to a filematrix | Row and column names | Closing filematrices | Open or load an existing filematrix | By column access is faster then by rows | Appending columns | Deleting filematrix files | Version information

Working with large matrices | Accessing all matrix elements | Filling in matrix values | Calculating column sums | Calculating row sums | Removing filematrix after use | Version information

Motivation for creation of filematrix package | Differences between filematrix and bigmemory packages | Differences in tests | Example when filematrix is much more efficient than bigmemory

Overview | Permutation analysis on matched binary data sets | Enrichment testing for two sets of p-values \ | Enrichment testing with shiftR | Matching data sets by location

Statistical model for Joint Analysis of Methylation and Genotype Data | Input data | Create data matrices for CpG-SNP analysis | SNP-CpG analysis

Loading and saving RaMWAS objects | QC text summary | Quality control measures | The number of BAM files | Total number of reads in the BAM file(s) | Number of reads aligned to the reference genome | Number of reads that passed minimum score filter | Number of reads after removal of duplicate reads | Number of recorded reads aligned to each strand | Distribution of the alignment scores | Distribution of the length of the aligned part of the reads | Distribution of edit distance | Number of reads away from CpGs | Average CpG score for CpGs and non-CpGs | Average CpG score vs. CpG density | Coverage around isolated CpGs | Fraction of reads from chrX and chrY