RLM: Fast and simplified extraction of Read-Level Methylation metrics from bisulfite sequencing data.
Ontology highlight
ABSTRACT:
Bisulfite sequencing data provide value beyond the straightforward methylation assessment by analyzing single-read patterns. Over the past years, various informative metrics have been established to explore this information. However, limited compatibility with alignment tools, reference genomes or the measurements they provide present a bottleneck for most groups to include this information as standard analysis. To address this, we developed RLM, a fast and scalable tool for the computation of frequently used Read-Level Methylation statistics. RLM supports several common alignment tools, works independently of the reference genome and handles all frequently used sequencing experiment designs. RLM can process large input files with a billion reads in just a few hours on common workstations.Availability
https://github.com/sarahet/RLM.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Hetzel S
PROVIDER: S-EPMC8686677 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Whole-genome bisulfite sequencing (WGBS) has emerged as the gold-standard technique in genome-scale studies of DNA methylation. Mapping reads from WGBS requires unique considerations that make the process more time-consuming than in other sequencing applications. Typical WGBS data sets contain several hundred million reads, adding to this analysis challenge. We present the WALT tool for mapping WGBS reads. WALT uses a strategy of hashing periodic spaced seeds, which leads to significant speedup compared with the most efficient methods currently available. Although many existing WGBS mappers slow down with read length, WALT improves in speed. Importantly, these speed gains do not sacrifice accuracy.Availability and implementationWALT is available under the GPL v3 license, and downloadable from https://github.com/smithlabcode/walt.Contactandrewds@usc.edu or tingchen@usc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
| S-EPMC5181568 | biostudies-literature
Project description:DNA methylation is an important epigenetic mark relevant to normal development and disease genesis. A common approach to characterizing genome-wide DNA methylation is using Next Generation Sequencing technology to sequence bisulfite treated DNA. The short sequence reads are mapped to the reference genome to determine the methylation statuses of Cs. However, despite intense effort, a much smaller proportion of the reads derived from bisulfite treated DNA (usually about 40-80%) can be mapped than regular short reads mapping (> 90%), and it is unclear what factors lead to this low mapping efficiency.To address this issue, we used the hairpin bisulfite sequencing technology to determine sequences of both DNA double strands simultaneously. This enabled the recovery of the original non-bisulfite-converted sequences. We used Bismark for bisulfite read mapping and Bowtie2 for recovered read mapping. We found that recovering the reads improved unique mapping efficiency by 9-10% compared to the bisulfite reads. Such improvement in mapping efficiency is related to sequence entropy.The hairpin recovery technique improves mapping efficiency, and sequence entropy relates to mapping efficiency.
| S-EPMC4652484 | biostudies-literature
Project description:BackgroundBisulfite sequencing is one of the most widely used technologies in analyzing DNA methylation patterns, which are important in understanding and characterizing the mechanism of DNA methylation and its functions in disease development. Efficient and user-friendly tools are critical in carrying out such analysis on high-throughput bisulfite sequencing data. However, existing tools are either not scalable well, or inadequate in providing visualization and other desirable functionalities.ResultsIn order to handle ultra large sequencing data and to provide additional functions and features, we have developed BSPAT, a fast online tool for bisulfite sequencing pattern analysis. With a user-friendly web interface, BSPAT seamlessly integrates read mapping/quality control/methylation calling with methylation pattern generation and visualization. BSPAT has the following important features: 1) instead of using multiple/pairwise sequence alignment methods, BSPAT adopts an efficient and widely used sequence mapping tool to provide fast alignment of sequence reads; 2) BSPAT summarizes and visualizes DNA methylation co-occurrence patterns at a single nucleotide level, which provide valuable information in understanding the mechanism and regulation of DNA methylation; 3) based on methylation co-occurrence patterns, BSPAT can automatically detect potential allele-specific methylation (ASM) patterns, which can greatly enhance the detection and analysis of ASM patterns; 4) by linking directly with other popular databases and tools, BSPAT allows users to perform integrative analysis of methylation patterns with other genomic features together within regions of interest.ConclusionBy utilizing a real bisulfite sequencing dataset generated from prostate cancer cell lines, we have shown that BSPAT is highly efficient. It has also reported some interesting methylation co-occurrence patterns and a potential allele-specific methylation case. In conclusion, BSPAT is an efficient and convenient tool for high-throughput bisulfite sequencing data analysis that can be broadly used.
| S-EPMC4499179 | biostudies-literature
Project description:Background: With advances in next-generation sequencing technologies, the bisulfite conversion of genomic DNA followed by sequencing has become the predominant technique for quantifying genome-wide DNA methylation at single-base resolution. A large number of computational approaches are available in literature for identifying differentially methylated regions in bisulfite sequencing data, and more are being developed continuously. Results: Here, we focused on a comprehensive evaluation of commonly used differential methylation analysis methods and describe the potential strengths and limitations of each method. We found that there are large differences among methods, and no single method consistently ranked first in all benchmarking. Moreover, smoothing seemed not to improve the performance greatly, and a small number of replicates created more difficulties in the computational analysis of BS-seq data than low sequencing depth. Conclusions: Data analysis and interpretation should be performed with great care, especially when the number of replicates or sequencing depth is limited.
| S-EPMC8345583 | biostudies-literature
Project description:MotivationEpigenome-wide association studies can provide novel insights into the regulation of genes involved in traits and diseases. The rapid emergence of bisulfite-sequencing technologies enables performing such genome-wide studies at the resolution of single nucleotides. However, analysis of data produced by bisulfite-sequencing poses statistical challenges owing to low and uneven sequencing depth, as well as the presence of confounding factors. The recently introduced Mixed model Association for Count data via data AUgmentation (MACAU) can address these challenges via a generalized linear mixed model when confounding can be encoded via a single variance component. However, MACAU cannot be used in the presence of multiple variance components. Additionally, MACAU uses a computationally expensive Markov Chain Monte Carlo (MCMC) procedure, which cannot directly approximate the model likelihood.ResultsWe present a new method, Mixed model Association via a Laplace ApproXimation (MALAX), that is more computationally efficient than MACAU and allows to model multiple variance components. MALAX uses a Laplace approximation rather than MCMC based approximations, which enables to directly approximate the model likelihood. Through an extensive analysis of simulated and real data, we demonstrate that MALAX successfully addresses statistical challenges introduced by bisulfite-sequencing while controlling for complex sources of confounding, and can be over 50% faster than the state of the art.Availability and implementationThe full source code of MALAX is available at https://github.com/omerwe/MALAX .Contactomerw@cs.technion.ac.il or ehalperin@cs.ucla.edu.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC5870555 | biostudies-literature
Project description:UnlabelledHere we present the open-source R/Bioconductor software package BEAT (BS-Seq Epimutation Analysis Toolkit). It implements all bioinformatics steps required for the quantitative high-resolution analysis of DNA methylation patterns from bisulfite sequencing data, including the detection of regional epimutation events, i.e. loss or gain of DNA methylation at CG positions relative to a reference. Using a binomial mixture model, the BEAT package aggregates methylation counts per genomic position, thereby compensating for low coverage, incomplete conversion and sequencing errors.Availability and implementationBEAT is freely available as part of Bioconductor at www.bioconductor.org/packages/devel/bioc/html/BEAT.html. The package is distributed under the GNU Lesser General Public License 3.0.
| S-EPMC4071208 | biostudies-literature
Project description:The detection of differentially methylated regions (DMRs) is a necessary prerequisite for characterizing different epigenetic states. We present a novel program, metilene, to identify DMRs within whole-genome and targeted data with unrivaled specificity and sensitivity. A binary segmentation algorithm combined with a two-dimensional statistical test allows the detection of DMRs in large methylation experiments with multiple groups of samples in minutes rather than days using off-the-shelf hardware. metilene outperforms other state-of-the-art tools for low coverage data and can estimate missing data. Hence, metilene is a versatile tool to study the effect of epigenetic modifications in differentiation/development, tumorigenesis, and systems biology on a global, genome-wide level. Whether in the framework of international consortia with dozens of samples per group, or even without biological replicates, it produces highly significant and reliable results.
| S-EPMC4728377 | biostudies-literature
Project description:Phased DNA methylation states within bisulfite sequencing reads are valuable source of information that can be used to estimate epigenetic diversity across cells as well as epigenomic instability in individual cells. Various measures capturing the heterogeneity of DNA methylation states have been proposed for a decade. However, in routine analyses on DNA methylation, this heterogeneity is often ignored by computing average methylation levels at CpG sites, even though such information exists in bisulfite sequencing data in the form of phased methylation states, or methylation patterns. In this study, to facilitate the application of the DNA methylation heterogeneity measures in downstream epigenomic analyses, we present a Rust-based, extremely fast and lightweight bioinformatics toolkit called Metheor. As the analysis of DNA methylation heterogeneity requires the examination of pairs or groups of CpGs throughout the genome, existing softwares suffer from high computational burden, which almost make a large-scale DNA methylation heterogeneity studies intractable for researchers with limited resources. In this study, we benchmark the performance of Metheor against existing code implementations for DNA methylation heterogeneity measures in three different scenarios of simulated bisulfite sequencing datasets. Metheor was shown to dramatically reduce the execution time up to 300-fold and memory footprint up to 60-fold, while producing identical results with the original implementation, thereby facilitating a large-scale study of DNA methylation heterogeneity profiles. To demonstrate the utility of the low computational burden of Metheor, we show that the methylation heterogeneity profiles of 928 cancer cell lines can be computed with standard computing resources. With those profiles, we reveal the association between DNA methylation heterogeneity and various omics features. Source code for Metheor is at https://github.com/dohlee/metheor and is freely available under the GPL-3.0 license.
| S-EPMC10062925 | biostudies-literature
Project description:BackgroundDNA methylation has essential roles in transcriptional regulation, imprinting, X chromosome inactivation and other cellular processes, and aberrant CpG methylation is directly involved in the pathogenesis of human imprinting disorders and many cancers. To address the need for a quantitative and highly multiplexed bisulfite sequencing method with long read lengths for targeted CpG methylation analysis, we developed single-molecule real-time bisulfite sequencing (SMRT-BS).ResultsOptimized bisulfite conversion and PCR conditions enabled the amplification of DNA fragments up to ~1.5 kb, and subjecting overlapping 625-1491 bp amplicons to SMRT-BS indicated high reproducibility across all amplicon lengths (r=0.972) and low standard deviations (≤0.10) between individual CpG sites sequenced in triplicate. Higher variability in CpG methylation quantitation was correlated with reduced sequencing depth, particularly for intermediately methylated regions. SMRT-BS was validated by orthogonal bisulfite-based microarray (r=0.906; 42 CpG sites) and second generation sequencing (r=0.933; 174 CpG sites); however, longer SMRT-BS amplicons (>1.0 kb) had reduced, but very acceptable, correlation with both orthogonal methods (r=0.836-0.897 and r=0.892-0.927, respectively) compared to amplicons less than ~1.0 kb (r=0.940-0.951 and r=0.948-0.963, respectively). Multiplexing utility was assessed by simultaneously subjecting four distinct CpG island amplicons (702-866 bp; 325 CpGs) and 30 hematological malignancy cell lines to SMRT-BS (average depth of 110X), which identified a spectrum of highly quantitative methylation levels across all interrogated CpG sites and cell lines.ConclusionsSMRT-BS is a novel, accurate and cost-effective targeted CpG methylation method that is amenable to a high degree of multiplexing with minimal clonal PCR artifacts. Increased sequencing depth is necessary when interrogating longer amplicons (>1.0 kb) and the previously reported bisulfite sequencing PCR bias towards unmethylated DNA should be considered when measuring intermediately methylated regions. Coupled with an optimized bisulfite PCR protocol, SMRT-BS is capable of interrogating ~1.5 kb amplicons, which theoretically can cover ~91% of CpG islands in the human genome.
| S-EPMC4422326 | biostudies-literature
Project description:Whole genome bisulfite sequencing is currently at the forefront of epigenetic analysis, facilitating the nucleotide-level resolution of 5-methylcytosine (5mC) on a genome-wide scale. Specialized software have been developed to accommodate the unique difficulties in aligning such sequencing reads to a given reference, building on the knowledge acquired from model organisms such as human, or Arabidopsis thaliana. As the field of epigenetics expands its purview to non-model plant species, new challenges arise which bring into question the suitability of previously established tools. Herein, nine short-read aligners are evaluated: Bismark, BS-Seeker2, BSMAP, BWA-meth, ERNE-BS5, GEM3, GSNAP, Last and segemehl. Precision-recall of simulated alignments, in comparison to real sequencing data obtained from three natural accessions, reveals on-balance that BWA-meth and BSMAP are able to make the best use of the data during mapping. The influence of difficult-to-map regions, characterized by deviations in sequencing depth over repeat annotations, is evaluated in terms of the mean absolute deviation of the resulting methylation calls in comparison to a realistic methylome. Downstream methylation analysis is responsive to the handling of multi-mapping reads relative to mapping quality (MAPQ), and potentially susceptible to bias arising from the increased sequence complexity of densely methylated reads.
| S-EPMC8425420 | biostudies-literature