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. 2016 Nov 25;17(1):484.
doi: 10.1186/s12859-016-1380-3.

ampliMethProfiler: a pipeline for the analysis of CpG methylation profiles of targeted deep bisulfite sequenced amplicons

Giovanni Scala  1 , Ornella Affinito  2   3 , Domenico Palumbo  2 , Ermanno Florio  2   3 , Antonella Monticelli  3 , Gennaro Miele  4   5 , Lorenzo Chiariotti  2   3 , Sergio Cocozza  2   3
Affiliations

ampliMethProfiler: a pipeline for the analysis of CpG methylation profiles of targeted deep bisulfite sequenced amplicons

Giovanni Scala et al. BMC Bioinformatics. .

Abstract

Background: CpG sites in an individual molecule may exist in a binary state (methylated or unmethylated) and each individual DNA molecule, containing a certain number of CpGs, is a combination of these states defining an epihaplotype. Classic quantification based approaches to study DNA methylation are intrinsically unable to fully represent the complexity of the underlying methylation substrate. Epihaplotype based approaches, on the other hand, allow methylation profiles of cell populations to be studied at the single molecule level. For such investigations, next-generation sequencing techniques can be used, both for quantitative and for epihaplotype analysis. Currently available tools for methylation analysis lack output formats that explicitly report CpG methylation profiles at the single molecule level and that have suited statistical tools for their interpretation.

Results: Here we present ampliMethProfiler, a python-based pipeline for the extraction and statistical epihaplotype analysis of amplicons from targeted deep bisulfite sequencing of multiple DNA regions.

Conclusions: ampliMethProfiler tool provides an easy and user friendly way to extract and analyze the epihaplotype composition of reads from targeted bisulfite sequencing experiments. ampliMethProfiler is written in python language and requires a local installation of BLAST and (optionally) QIIME tools. It can be run on Linux and OS X platforms. The software is open source and freely available at http://amplimethprofiler.sourceforge.net .

Keywords: Bisulfite sequencing; DNA methylation; Epihaplotype; Epihaplotype based analysis; Methylation profiles.

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Figures

Fig. 1
Fig. 1
ampliMethProfiler workflow. Functional modules are represented as trapezes. Input and output files are represented as dashed and solid rectangles, respectively
Fig. 2
Fig. 2
ampliMethProfiler output files. a Content example of a summary and quality statistics file. b Content example of a plain text alignment file. c Content example of a methylation profiles file. d Content example of a methylation profile abundances file
Fig. 3
Fig. 3
Profile abundances plots. a Profile composition summary charts. Bar charts representing relative abundances of profiles grouped by number of methylated CpGs. b Heatmap representing methylation profile abundances in each sample
Fig. 4
Fig. 4
Alpha diversity rarefaction plots at sample level (right column) and developmental stage level (left column)
Fig. 5
Fig. 5
Beta diversity plots. a 3D Emperor plot snapshot representing the first three principal components of the PCoA. b From left to right are reported: Bray-Curtis distance boxplots of pairwise distances computed between samples from the same developmental stage, pairwise distances computed between pairs of samples from different developmental stages, distances within P90 mice, distances within P0 mice and distances between pairs of P90 and P0 mice
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References

    1. Beygo J, Ammerpohl O, Gritzan D, Heitmann M, Rademacher K, Richter J, Caliebe A, Siebert R, Horsthemke B, Buiting K. Deep Bisulfite Sequencing of Aberrantly Methylated Loci in a Patient with Multiple Methylation Defects. PLoS One. 2013;8(10):e76953. doi: 10.1371/journal.pone.0076953. - DOI - PMC - PubMed
    1. Taylor K, Kramer R, Davis J, Guo J, Duff D, Xu D, Caldwell C, Shi H. Ultradeep Bisulfite Sequencing Analysis of DNA Methylation Patterns in Multiple Gene Promoters by 454 Sequencing. Cancer Res. 2007;67(18):8511–8518. doi: 10.1158/0008-5472.CAN-07-1016. - DOI - PubMed
    1. Mikeska T, Candiloro I, Dobrovic A. The implications of heterogeneous DNA methylation for the accurate quantification of methylation. Epigenomics. 2010;2(4):561–573. doi: 10.2217/epi.10.32. - DOI - PubMed
    1. Landan G, Cohen N, Mukamel Z, Bar A, Molchadsky A, Brosh R, Horn-Saban S, Zalcenstein D, Goldfinger N, Zundelevich A, et al. Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues. Nat Genet. 2012;44(11):1207–1214. doi: 10.1038/ng.2442. - DOI - PubMed
    1. Dolinoy D, Das R, Weidman J, Jirtle R. Metastable Epialleles, Imprinting, and the Fetal Origins of Adult Diseases. Pediatr Res. 2007;61(5 Part 2):30R–37R. doi: 10.1203/pdr.0b013e31804575f7. - DOI - PubMed

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