Resources


Software   
chromstaR

Description 
chromstaR is a versatile computational algorithm for the analysis of single and/or multiple ChIP-seq experiments with or without replicates. The main motivation behind the algorithm is to be able to 1) infer combinatorial chromatin state maps based on ChIP-seq measurements of different histone modifications, or 2) detect changes in combinatorial chromatin state maps across different conditions such as experimental treatments, tissues, or developmental time points. However, chromstaR can also be applied to more standard data analysis problems such as 1) analysis of ChIP-seq measurements of a single histone modification, or 2) comparison of ChIP-seq profiles of a single histone modification measured in different conditions, such as experimental treatments, tissues, or developmental time points.

Reference
Taudt A, Nguyen MA, Heinig M, Johannes F, Colomé-Tatché M.
chromstaR: Tracking combinatorial chromatin states in space and time.
bioRxiv 
doi: http://dx.doi.org/10.1101/038612

Availability





Software   
methIMPUTE

Description 
Whole-genome Bisulfite sequencing (WGBS) has become the standard method for interrogating plant methylomes at base resolution. However, deep WGBS measurements remain cost prohibitive for large, complex genomes and for population-level studies. As a result, most published plant methylomes are sequenced far below saturation, with a large proportion of cytosines having either missing data or insufficient coverage. Here we present METHimpute, a Hidden Markov Model (HMM) based imputation algorithm for the analysis of WGBS data. Unlike existing methods, METHimpute enables the construction of complete methylomes by inferring the methylation status and level of all cytosines in the genome regardless of coverage. Application of METHimpute to maize, rice and Arabidopsis shows that the algorithm infers cytosine-resolution methylomes with high accuracy from data as low as 6X, compared to data with 60X, thus making it a cost-effective solution for large-scale studies. Although METHimpute has been extensively tested in plants, it should be broadly applicable to other species.

Reference
Taudt A, Roquis D, Vidalis A, Wardenaar R, Johannes F*, Colomé-Tatché M*.
METHimpute: Imputation-guided construction of complete methylomes from WGBS data.
bioRxiv
doi: https://doi.org/10.1101/190223

Availability

Bioconductor R package