A Comparison of the Whole Genome Approach of MeDIP-Seq to the Targeted Approach of the Infinium HumanMethylation450 BeadChip® for Methylome Profiling
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{"title"=>"A Comparison of the Whole Genome Approach of MeDIP-Seq to the Targeted Approach of the Infinium HumanMethylation450 BeadChip® for Methylome Profiling", "type"=>"journal", "authors"=>[{"first_name"=>"Christine", "last_name"=>"Clark", "scopus_author_id"=>"56424726400"}, {"first_name"=>"Priit", "last_name"=>"Palta", "scopus_author_id"=>"23012599400"}, {"first_name"=>"Christopher J.", "last_name"=>"Joyce", "scopus_author_id"=>"56530289900"}, {"first_name"=>"Carol", "last_name"=>"Scott", "scopus_author_id"=>"7403430044"}, {"first_name"=>"Elin", "last_name"=>"Grundberg", "scopus_author_id"=>"6506067746"}, {"first_name"=>"Panos", "last_name"=>"Deloukas", "scopus_author_id"=>"7003287098"}, {"first_name"=>"Aarno", "last_name"=>"Palotie", "scopus_author_id"=>"7005614368"}, {"first_name"=>"Alison J.", "last_name"=>"Coffey", "scopus_author_id"=>"7005763709"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84870525593", "sgr"=>"84870525593", "pui"=>"366195702", "isbn"=>"10.1371/journal.pone.0050233", "pmid"=>"23209683", "doi"=>"10.1371/journal.pone.0050233"}, "id"=>"80deac54-a373-36e5-8a48-2b40c9874003", "abstract"=>"DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.", "link"=>"http://www.mendeley.com/research/comparison-whole-genome-approach-medipseq-targeted-approach-infinium-humanmethylation450-beadchip-me", "reader_count"=>133, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>10, "Librarian"=>1, "Researcher"=>29, "Student > Doctoral Student"=>11, "Student > Ph. D. Student"=>42, "Student > Postgraduate"=>2, "Student > Master"=>12, "Other"=>4, "Student > Bachelor"=>9, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>3, "Professor"=>5}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>10, "Librarian"=>1, "Researcher"=>29, "Student > Doctoral Student"=>11, "Student > Ph. D. Student"=>42, "Student > Postgraduate"=>2, "Student > Master"=>12, "Other"=>4, "Student > Bachelor"=>9, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>3, "Professor"=>5}, "reader_count_by_subject_area"=>{"Unspecified"=>6, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>20, "Agricultural and Biological Sciences"=>80, "Medicine and Dentistry"=>17, "Philosophy"=>1, "Neuroscience"=>3, "Psychology"=>1, "Computer Science"=>4}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>17}, "Neuroscience"=>{"Neuroscience"=>3}, "Psychology"=>{"Psychology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>80}, "Computer Science"=>{"Computer Science"=>4}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>20}, "Unspecified"=>{"Unspecified"=>6}, "Environmental Science"=>{"Environmental Science"=>1}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"South Korea"=>1, "Sweden"=>1, "Turkey"=>1, "United States"=>2, "Luxembourg"=>1, "China"=>2, "Finland"=>1, "United Kingdom"=>2, "Switzerland"=>1, "Germany"=>1, "India"=>1}, "group_count"=>8}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/287819", "https://ndownloader.figshare.com/files/287914", "https://ndownloader.figshare.com/files/287968", "https://ndownloader.figshare.com/files/288049", "https://ndownloader.figshare.com/files/288135", "https://ndownloader.figshare.com/files/288237", "https://ndownloader.figshare.com/files/288287", "https://ndownloader.figshare.com/files/288360", "https://ndownloader.figshare.com/files/288387", "https://ndownloader.figshare.com/files/288406"], "description"=>"<div><p>DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.</p> </div>", "links"=>[], "tags"=>["genome", "medip-seq", "targeted", "infinium", "humanmethylation450", "methylome", "profiling"], "article_id"=>116700, "categories"=>["Molecular Biology", "Physics", "Biochemistry", "Biophysics", "Biological Sciences", "Genetics"], "users"=>["Christine Clark", "Priit Palta", "Christopher J. Joyce", "Carol Scott", "Elin Grundberg", "Panos Deloukas", "Aarno Palotie", "Alison J. Coffey"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0050233.s001", "https://dx.doi.org/10.1371/journal.pone.0050233.s002", "https://dx.doi.org/10.1371/journal.pone.0050233.s003", "https://dx.doi.org/10.1371/journal.pone.0050233.s004", "https://dx.doi.org/10.1371/journal.pone.0050233.s005", "https://dx.doi.org/10.1371/journal.pone.0050233.s006", "https://dx.doi.org/10.1371/journal.pone.0050233.s007", "https://dx.doi.org/10.1371/journal.pone.0050233.s008", "https://dx.doi.org/10.1371/journal.pone.0050233.s009", "https://dx.doi.org/10.1371/journal.pone.0050233.s010"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/A_Comparison_of_the_Whole_Genome_Approach_of_MeDIP_Seq_to_the_Targeted_Approach_of_the_Infinium_HumanMethylation450_BeadChip_for_Methylome_Profiling__/116700", "title"=>"A Comparison of the Whole Genome Approach of MeDIP-Seq to the Targeted Approach of the Infinium HumanMethylation450 BeadChip<sup>®</sup> for Methylome Profiling", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-11-29 01:51:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/534365"], "description"=>"<p>The different features are described along the bottom axis. 100% coverage is defined as covering all of the elements of a particular type in the human genome. Coverage for MeDIP-seq data (MD-s) (averaged for GM01240 and GM01247) is shown as blue bars and for the HumanMethylation 450K (450K) as red bars. Average percentages covered for each technique for each group of features are given above the bar chart. For MeDIP-seq the region or feature was defined as being covered if any part of the region or feature was covered by or overlapped any part of one or more sequencing reads. The coverage for the MeDIP-seq was consistent between the two samples (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050233#pone.0050233.s005\" target=\"_blank\">Table S1</a>), illustrating a high degree of reproducibility for the technique. The coverage shown for the HumanMethylation 450K is reported as the number of features where at least one probe present on the array mapped within the features under consideration i.e. is based on the array design.</p>", "links"=>[], "tags"=>["medip-seq", "humanmethylation", "450k", "beadchip", "genomic"], "article_id"=>204843, "categories"=>["Molecular Biology", "Physics", "Biochemistry", "Biophysics", "Biological Sciences", "Genetics"], "users"=>["Christine Clark", "Priit Palta", "Christopher J. Joyce", "Carol Scott", "Elin Grundberg", "Panos Deloukas", "Aarno Palotie", "Alison J. Coffey"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0050233.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Coverage_by_MeDIP_seq_and_the_HumanMethylation_450K_BeadChip_of_different_genomic_features_/204843", "title"=>"Coverage by MeDIP-seq and the HumanMethylation 450K BeadChip of different genomic features.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-29 01:20:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/534452"], "description"=>"<p>Data are shown for the 28 islands (associated with 36 genes) containing CpG sites that overlapped with those interrogated by HumanMethylation 450K array for sample GM01240. Evolutionary strata information is shown to the right of the ideogram of the human X chromosome <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050233#pone.0050233-Ross1\" target=\"_blank\">[66]</a>: the blue line represents the S3 stratum; the purple line represents the S2 stratum and the red line the S1 stratum. Both names are given for genes sharing a CpG island separated by “/”. Methylation level estimates for each of the techniques are shown to the right of the gene names in light green (low), green (medium), and dark green (high). Examples of four genes are shown in more detail on the right of the figure. The gene names are highlighted in colour at the top of each panel and in a corresponding colour on the gene list. Data for the bisulfite sequencing (BS-s), HumanMethylation 450K (450K) and MeDIP-seq (MD-s) are shown at the top, center and bottom of each panel, respectively. The genes shown give examples where the three techniques agree in methylation level: low level methylation in the gene ZFX, medium level methylation in the PRPS2 gene, and a high level of methylation in the ACRC gene. Data are also given for the HCFC1/TMEM187 genes, for which different methods show inconsistency in the classified methylation levels. See <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050233#pone.0050233.s004\" target=\"_blank\">Figure S4</a> for data for sample GM01247.</p>", "links"=>[], "tags"=>["methylation", "estimates", "bisulfite", "humanmethylation", "450k", "medip-seq"], "article_id"=>204933, "categories"=>["Molecular Biology", "Physics", "Biochemistry", "Biophysics", "Biological Sciences", "Genetics"], "users"=>["Christine Clark", "Priit Palta", "Christopher J. Joyce", "Carol Scott", "Elin Grundberg", "Panos Deloukas", "Aarno Palotie", "Alison J. Coffey"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0050233.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_methylation_level_estimates_for_the_bisulfite_sequencing_HumanMethylation_450K_and_MeDIP_seq_data_/204933", "title"=>"Comparison of methylation level estimates for the bisulfite sequencing, HumanMethylation 450K and MeDIP-seq data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-29 01:22:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/534598"], "description"=>"<p>(A) The numbers of methylation variable positions (MVPs) detected the by the 450K array (autosomal and X) are given in the red circle, and the number of differentially methylated regions (DMRs) detected with MD-s in the blue circle. The number of differentially methylated loci detected by both methods is given in the intersection of the two circles. Any DMR detected by MD-s within this intersection contained one or more significant MVP(s) detected by the 450K array. (B) Location with respect to different genomic features of the differentially methylated regions detected by both methods (see key to the bottom right of the figure for the genomic feature represented by each colour). (C) Exact number of and location with respect to different genomic features of the DMRs detected by MD-s only. (D) Exact number of and location with respect to different genomic features of the MVPs detected by 450K only. It is important to note that many of the genomic elements overlap with each other. Additionally, in the case of the DMRs found by MD-s, many of the longer DMRs span several different genomic features.</p>", "links"=>[], "tags"=>["methylated", "loci", "humanmethylation", "450k", "medip-seq"], "article_id"=>205078, "categories"=>["Molecular Biology", "Physics", "Biochemistry", "Biophysics", "Biological Sciences", "Genetics"], "users"=>["Christine Clark", "Priit Palta", "Christopher J. Joyce", "Carol Scott", "Elin Grundberg", "Panos Deloukas", "Aarno Palotie", "Alison J. Coffey"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0050233.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Differentially_methylated_loci_detected_by_the_HumanMethylation_450K_array_450K_and_MeDIP_seq_MD_s_/205078", "title"=>"Differentially methylated loci detected by the HumanMethylation 450K array (450K) and MeDIP-seq (MD-s).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-29 01:24:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/534709"], "description"=>"<p>The methylation levels for each individual CpG site assayed by the bisulfite data (BS-s) were classified as low, medium or high based on the output from MethTools. The boundaries for low, medium and high methylation intervals for each probe for the HumanMethylation 450K array (450K) and corresponding window for the MEDIPS data were determined by comparison to the bisulfite sequencing data. In the top part of the table the concordance between these intervals was calculated for all overlapping loci from the different methods for the regions covered by the bisulfite data. The second half of the table contains the concordance for a similar analysis for all autosomal chromosomes for the MeDIP-seq (MD-s) and HumanMethylation 450K data.</p>", "links"=>[], "tags"=>["humanmethylation", "450k", "medip-seq", "bisulfite", "sequencing", "interval-based"], "article_id"=>205197, "categories"=>["Molecular Biology", "Physics", "Biochemistry", "Biophysics", "Biological Sciences", "Genetics"], "users"=>["Christine Clark", "Priit Palta", "Christopher J. Joyce", "Carol Scott", "Elin Grundberg", "Panos Deloukas", "Aarno Palotie", "Alison J. Coffey"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0050233.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Concordance_of_the_HumanMethylation_450K_450K_and_MeDIP_seq_MD_s_data_with_bisulfite_sequencing_BS_s_data_using_an_interval_based_approach_/205197", "title"=>"Concordance of the HumanMethylation 450K (450K) and MeDIP-seq (MD-s) data with bisulfite sequencing (BS-s) data using an interval-based approach.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-11-29 01:26:37"}
  • {"files"=>["https://ndownloader.figshare.com/files/534746"], "description"=>"<p>The top part of the table gives the concordance of the average beta-values for the 326 probes on the X chromosome from the HumanMethylation 450K (450K) and the methylation score calculated by the MEDIPS software for the MeDIP-seq data (MD-s) to the methylation levels for the bisulfite data (BS-s) from MethTools. The second half of the table contains the concordance for a similar analysis for the HumanMethylation 450K and MeDIP-seq data for all autosomal chromosomes.</p>", "links"=>[], "tags"=>["humanmethylation", "450k", "medip-seq", "bisulfite", "sequencing"], "article_id"=>205233, "categories"=>["Molecular Biology", "Physics", "Biochemistry", "Biophysics", "Biological Sciences", "Genetics"], "users"=>["Christine Clark", "Priit Palta", "Christopher J. Joyce", "Carol Scott", "Elin Grundberg", "Panos Deloukas", "Aarno Palotie", "Alison J. Coffey"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0050233.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Concordance_of_the_HumanMethylation_450K_450K_and_MeDIP_seq_MD_s_data_with_bisulfite_sequencing_BS_s_data_/205233", "title"=>"Concordance of the HumanMethylation 450K (450K) and MeDIP-seq (MD-s) data with bisulfite sequencing (BS-s) data.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-11-29 01:27:13"}

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Relative Metric

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