MatrixEQTL - Matrix eQTL: Ultra Fast eQTL Analysis via Large Matrix Operations

Matrix eQTL is designed for fast eQTL analysis on large datasets. Matrix eQTL can test for association between genotype and gene expression using linear regression with either additive or ANOVA genotype effects. The models can include covariates to account for factors as population stratification, gender, and clinical variables. It also supports models with heteroscedastic and/or correlated errors, false discovery rate estimation and separate treatment of local (cis) and distant (trans) eQTLs. For more details see Shabalin (2012) <doi:10.1093/bioinformatics/bts163>.

Last updated 1 years ago

8.06 score 61 stars 2 packages 628 scripts 681 downloads

filematrix - File-Backed Matrix Class with Convenient Read and Write Access

Interface for working with large matrices stored in files, not in computer memory. Supports multiple non-character data types (double, integer, logical and raw) of various sizes (e.g. 8 and 4 byte real values). Access to parts of the matrix is done by indexing, exactly as with usual R matrices. Supports very large matrices. Tested on multi-terabyte matrices. Allows for more than 2^32 rows or columns. Allows for quick addition of extra columns to a filematrix. Cross-platform as the package has R code only.

Last updated 6 years ago

6.51 score 8 stars 2 packages 45 scripts 410 downloads

ramwas - Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms

A complete toolset for methylome-wide association studies (MWAS). It is specifically designed for data from enrichment based methylation assays, but can be applied to other data as well. The analysis pipeline includes seven steps: (1) scanning aligned reads from BAM files, (2) calculation of quality control measures, (3) creation of methylation score (coverage) matrix, (4) principal component analysis for capturing batch effects and detection of outliers, (5) association analysis with respect to phenotypes of interest while correcting for top PCs and known covariates, (6) annotation of significant findings, and (7) multi-marker analysis (methylation risk score) using elastic net. Additionally, RaMWAS include tools for joint analysis of methlyation and genotype data. This work is published in Bioinformatics, Shabalin et al. (2018) <doi:10.1093/bioinformatics/bty069>.

Last updated 24 days ago

dnamethylationsequencingqualitycontrolcoveragepreprocessingnormalizationbatcheffectprincipalcomponentdifferentialmethylationvisualization

5.44 score 9 stars 22 scripts 260 downloads

shiftR - Fast Enrichment Analysis via Circular Permutations

Fast enrichment analysis for locally correlated statistics via circular permutations. The analysis can be performed at multiple significance thresholds for both primary and auxiliary data sets with efficient correction for multiple testing.

Last updated 6 years ago

4.04 score 1 stars 11 scripts 120 downloads