Project description:Affinity capture of DNA methylation combined with high-throughput sequencing strikes a good balance between the high cost of whole genome bisulfite sequencing and the low coverage of methylation arrays. We present BayMeth, an empirical Bayes approach that uses a fully methylated control sample to transform observed read counts into regional methylation levels. In our model, inefficient capture can readily be distinguished from low methylation levels. BayMeth improves on existing methods, allows explicit modeling of copy number variation, and offers computationally-efficient analytical mean and variance estimators. BayMeth is available in the Repitools Bioconductor package.
Project description:Affinity capture of DNA methylation combined with high-throughput sequencing strikes a good balance between the high cost of whole genome bisulfite sequencing and the low coverage of methylation arrays. We present BayMeth, an empirical Bayes approach that uses a fully methylated control sample to transform observed read counts into regional methylation levels. In our model, inefficient capture can readily be distinguished from low methylation levels. BayMeth improves on existing methods, allows explicit modeling of copy number variation, and offers computationally-efficient analytical mean and variance estimators. BayMeth is available in the Repitools Bioconductor package. Benchmarking samples to compare MBD- and MeDIP-seq [GSE38679, GSE24546; PMID 21045081] datasets against 450k measurements
Project description:In order to validate of CNV detection from low-coverage whole-genome sequencing in the blood samples from recurrent miscarriage couples, we employed a customized array Comparative Genomics Hybridization (aCGH, Agilent) approach as chromosomal microarray analysis (CMA) in present study for a cohort of 78 DNA samples from blood. CMA results were compared with low-coverage whole-genome sequencing detection results. 100% consistency was obtained in pathogenic or likely pathogenic CNVs detection.
Project description:Low coverage whole genome sequencing (lc-WGS) from inducible Tet TKO (Tet iTKO) and control (Ctrl) mouse ESCs (mESC), as well as for germline Dnmt TKO mESCs. mESCs were sorted to isolate the Live/Dead dye and Thy1.2 negative CD326+GFP+ population representing the mESCs populations responsive to the tamoxifen treatment. The cells were resuspended in FACS buffer and filtered with a 70 µM filter before sorting. These bulk-population samples were analyzed by using low coverage Whole Genome Sequencing (lc-WGS).
