A Quantitative Comparison of Single-Cell Whole Genome Amplification Methods
Publication Date
August 19, 2014
Journal
PLOS ONE
Authors
Charles F. A. De Bourcy, Iwijn De Vlaminck, Jad N. Kanbar, Jianbin Wang, et al
Volume
9
Issue
8
Pages
e105585
DOI
https://dx.plos.org/10.1371/journal.pone.0105585
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0105585
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/25136831
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4138190
Europe PMC
http://europepmc.org/abstract/MED/25136831
Web of Science
000340742100109
Scopus
84920645442
Mendeley
http://www.mendeley.com/research/quantitative-comparison-singlecell-whole-genome-amplification-methods
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Mendeley | Further Information

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CrossRef

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1642166"], "description"=>"<p>Overview of experiments, where n denotes the number of experiments of a given type. In the “<i>E. coli</i> single cells” column, the box that straddles both the “Microfluidic” and the “Tube” fields corresponds to the method of carrying out a first round of amplification in a microfluidic chamber and then a second round of amplification in a test tube. This method will be denoted by “microfluidic+tube” in subsequent figure captions.</p>", "links"=>[], "tags"=>["detection", "Genome Amplification Methods", "background contamination", "sequencing workflows", "error rates", "mda", "coverage uniformity", "Amplification Cycles", "Quantitative Comparison", "WGA methods", "genomic heterogeneity", "reaction gain", "Whole genome amplification", "Multiple Displacement Amplification", "coli DNA", "WGA kit", "MALBAC"], "article_id"=>1144899, "categories"=>["Biological Sciences"], "users"=>["Charles F. A. de Bourcy", "Iwijn De Vlaminck", "Jad N. Kanbar", "Jianbin Wang", "Charles Gawad", "Stephen R. Quake"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105585.g001", "stats"=>{"downloads"=>0, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Design_of_experiments_/1144899", "title"=>"Design of experiments.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-19 03:36:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/1642180"], "description"=>"<p>Main panel: Experimental error rates D versus gain G, for low gains. Here D is the fraction of bases differing from the reference in the mapped reads. Linear fits for D as a function of are also shown: their slope approximately indicates the per-base per-cycle replication error rate. Inset: D versus G over the entire gain range. Filled symbols signify bulk experiments, open symbols single-cell experiments.</p>", "links"=>[], "tags"=>["detection", "Genome Amplification Methods", "background contamination", "sequencing workflows", "error rates", "mda", "coverage uniformity", "Amplification Cycles", "Quantitative Comparison", "WGA methods", "genomic heterogeneity", "reaction gain", "Whole genome amplification", "Multiple Displacement Amplification", "coli DNA", "WGA kit", "MALBAC"], "article_id"=>1144913, "categories"=>["Biological Sciences"], "users"=>["Charles F. A. de Bourcy", "Iwijn De Vlaminck", "Jad N. Kanbar", "Jianbin Wang", "Charles Gawad", "Stephen R. Quake"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105585.g005", "stats"=>{"downloads"=>0, "page_views"=>24, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Combined_single_nucleotide_error_rates_/1144913", "title"=>"Combined single-nucleotide error rates.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-19 03:36:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/1642178"], "description"=>"<p>Size of resolvable duplications (W, minimum width of a sliding window average filter that gives rise to a relative genome mapping density smaller than 2 across all positions in the genome) versus gain. Filled symbols signify bulk experiments, open symbols single-cell experiments.</p>", "links"=>[], "tags"=>["detection", "Genome Amplification Methods", "background contamination", "sequencing workflows", "error rates", "mda", "coverage uniformity", "Amplification Cycles", "Quantitative Comparison", "WGA methods", "genomic heterogeneity", "reaction gain", "Whole genome amplification", "Multiple Displacement Amplification", "coli DNA", "WGA kit", "MALBAC"], "article_id"=>1144911, "categories"=>["Biological Sciences"], "users"=>["Charles F. A. de Bourcy", "Iwijn De Vlaminck", "Jad N. Kanbar", "Jianbin Wang", "Charles Gawad", "Stephen R. Quake"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105585.g004", "stats"=>{"downloads"=>0, "page_views"=>28, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_CNV_resolution_/1144911", "title"=>"CNV resolution.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-19 03:36:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/1642177"], "description"=>"<p>(A) Local mapping density from properly mapped reads (at fixed 5x sampling depth), normalized to average 1, as a function of position along the reference sequence, for single-cell MDA (microfluidic in red, microfluidic+tube in orange). (B) Same as panel A, but for single-cell MALBAC and bulk NEB-WGA. (C) Fractional genome coverage from properly mapped read pairs, plotted as a function of gain. Here, each set of properly mapped read pairs was randomly down-sampled to 5x depth. Experiments that did not generate this many properly mapped reads were not included in the figure. (D) Fraction of the genome covered by mapped read pairs when the set of <i>raw</i> read pairs was down-sampled to a fixed depth of 20x, plotted as a function of gain. Filled symbols signify bulk experiments, open symbols single-cell experiments.</p>", "links"=>[], "tags"=>["detection", "Genome Amplification Methods", "background contamination", "sequencing workflows", "error rates", "mda", "coverage uniformity", "Amplification Cycles", "Quantitative Comparison", "WGA methods", "genomic heterogeneity", "reaction gain", "Whole genome amplification", "Multiple Displacement Amplification", "coli DNA", "WGA kit", "MALBAC"], "article_id"=>1144910, "categories"=>["Biological Sciences"], "users"=>["Charles F. A. de Bourcy", "Iwijn De Vlaminck", "Jad N. Kanbar", "Jianbin Wang", "Charles Gawad", "Stephen R. Quake"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105585.g003", "stats"=>{"downloads"=>0, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Amplification_bias_and_uniformity_/1144910", "title"=>"Amplification bias and uniformity.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-19 03:36:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/1642174"], "description"=>"<p>(A) Breakdown of read pairs in each experiment according to type of mapping achieved. (B) Breakdown of unmapped reads by organism of origin, expressed as a fraction of the total number of reads.</p>", "links"=>[], "tags"=>["detection", "Genome Amplification Methods", "background contamination", "sequencing workflows", "error rates", "mda", "coverage uniformity", "Amplification Cycles", "Quantitative Comparison", "WGA methods", "genomic heterogeneity", "reaction gain", "Whole genome amplification", "Multiple Displacement Amplification", "coli DNA", "WGA kit", "MALBAC"], "article_id"=>1144907, "categories"=>["Biological Sciences"], "users"=>["Charles F. A. de Bourcy", "Iwijn De Vlaminck", "Jad N. Kanbar", "Jianbin Wang", "Charles Gawad", "Stephen R. Quake"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105585.g002", "stats"=>{"downloads"=>0, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sequence_read_classification_/1144907", "title"=>"Sequence read classification.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-19 03:36:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/1642186", "https://ndownloader.figshare.com/files/1642187", "https://ndownloader.figshare.com/files/1642188", "https://ndownloader.figshare.com/files/1642189"], "description"=>"<div><p>Single-cell sequencing is emerging as an important tool for studies of genomic heterogeneity. Whole genome amplification (WGA) is a key step in single-cell sequencing workflows and a multitude of methods have been introduced. Here, we compare three state-of-the-art methods on both bulk and single-cell samples of <i>E. coli</i> DNA: Multiple Displacement Amplification (MDA), Multiple Annealing and Looping Based Amplification Cycles (MALBAC), and the PicoPLEX single-cell WGA kit (NEB-WGA). We considered the effects of reaction gain on coverage uniformity, error rates and the level of background contamination. We compared the suitability of the different WGA methods for the detection of copy-number variations, for the detection of single-nucleotide polymorphisms and for <i>de-novo</i> genome assembly. No single method performed best across all criteria and significant differences in characteristics were observed; the choice of which amplifier to use will depend strongly on the details of the type of question being asked in any given experiment.</p></div>", "links"=>[], "tags"=>["detection", "Genome Amplification Methods", "background contamination", "sequencing workflows", "error rates", "mda", "coverage uniformity", "Amplification Cycles", "Quantitative Comparison", "WGA methods", "genomic heterogeneity", "reaction gain", "Whole genome amplification", "Multiple Displacement Amplification", "coli DNA", "WGA kit", "MALBAC"], "article_id"=>1144919, "categories"=>["Biological Sciences"], "users"=>["Charles F. A. de Bourcy", "Iwijn De Vlaminck", "Jad N. Kanbar", "Jianbin Wang", "Charles Gawad", "Stephen R. Quake"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0105585.s001", "https://dx.doi.org/10.1371/journal.pone.0105585.s002", "https://dx.doi.org/10.1371/journal.pone.0105585.s003", "https://dx.doi.org/10.1371/journal.pone.0105585.s004"], "stats"=>{"downloads"=>1, "page_views"=>42, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_Quantitative_Comparison_of_Single_Cell_Whole_Genome_Amplification_Methods_/1144919", "title"=>"A Quantitative Comparison of Single-Cell Whole Genome Amplification Methods", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-08-19 03:36:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/1642181"], "description"=>"<p>LG50, the minimal number of assembled contigs (≥500 bp) needed to cover 50% of the <i>E. coli</i> reference genome, versus reaction gain (at fixed raw sequencing depth 30x). Assemblies that failed to cover 50% of the reference sequence were symbolically assigned the maximum value that LG50 can take in this scenario ((50%•genome length/500) = 4686). Filled symbols signify bulk experiments, open symbols single-cell experiments.</p>", "links"=>[], "tags"=>["detection", "Genome Amplification Methods", "background contamination", "sequencing workflows", "error rates", "mda", "coverage uniformity", "Amplification Cycles", "Quantitative Comparison", "WGA methods", "genomic heterogeneity", "reaction gain", "Whole genome amplification", "Multiple Displacement Amplification", "coli DNA", "WGA kit", "MALBAC"], "article_id"=>1144914, "categories"=>["Biological Sciences"], "users"=>["Charles F. A. de Bourcy", "Iwijn De Vlaminck", "Jad N. Kanbar", "Jianbin Wang", "Charles Gawad", "Stephen R. Quake"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105585.g006", "stats"=>{"downloads"=>0, "page_views"=>23, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_De_novo_assemblies_/1144914", "title"=>"De-novo assemblies.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-19 03:36:46"}

PMC Usage Stats | Further Information

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Relative Metric

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