CiteULike | Further Information

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Mendeley | Further Information

{"title"=>"A modified method for whole exome resequencing from minimal amounts of starting DNA", "type"=>"journal", "authors"=>[{"first_name"=>"Iwanka", "last_name"=>"Kozarewa", "scopus_author_id"=>"14048845400"}, {"first_name"=>"Juan Manuel", "last_name"=>"Rosa-Rosa", "scopus_author_id"=>"14424466500"}, {"first_name"=>"Christopher P.", "last_name"=>"Wardell", "scopus_author_id"=>"6506097122"}, {"first_name"=>"Brian A.", "last_name"=>"Walker", "scopus_author_id"=>"56384903600"}, {"first_name"=>"Kerry", "last_name"=>"Fenwick", "scopus_author_id"=>"8690638400"}, {"first_name"=>"Ioannis", "last_name"=>"Assiotis", "scopus_author_id"=>"42260943100"}, {"first_name"=>"Costas", "last_name"=>"Mitsopoulos", "scopus_author_id"=>"6508208267"}, {"first_name"=>"Marketa", "last_name"=>"Zvelebil", "scopus_author_id"=>"7004486825"}, {"first_name"=>"Gareth J.", "last_name"=>"Morgan", "scopus_author_id"=>"56814258400"}, {"first_name"=>"Alan", "last_name"=>"Ashworth", "scopus_author_id"=>"35379025100"}, {"first_name"=>"Christopher J.", "last_name"=>"Lord", "scopus_author_id"=>"7101632397"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84857765412", "sgr"=>"84857765412", "pui"=>"364370636", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"22403682", "doi"=>"10.1371/journal.pone.0032617"}, "id"=>"e1440b7d-b5d4-3338-b966-59ed41d92f49", "abstract"=>"Next generation DNA sequencing (NGS) technologies have revolutionized the pace at which whole genome and exome sequences can be generated. However, despite these advances, many of the methods for targeted resequencing, such as the generation of high-depth exome sequences, are somewhat limited by the relatively large amounts of starting DNA that are normally required. In the case of tumour analysis this is particularly pertinent as many tumour biopsies often return submicrogram quantities of DNA, especially when tumours are microdissected prior to analysis. Here, we present a method for exome capture and resequencing using as little as 50 ng of starting DNA. The sequencing libraries generated by this minimal starting amount (MSA-Cap) method generate datasets that are comparable to standard amount (SA) whole exome libraries that use three micrograms of starting DNA. This method, which can be performed in most laboratories using commonly available reagents, has the potential to enhance large scale profiling efforts such as the resequencing of tumour exomes.", "link"=>"http://www.mendeley.com/research/modified-method-whole-exome-resequencing-minimal-amounts-starting-dna", "reader_count"=>85, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Researcher"=>30, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>18, "Student > Postgraduate"=>2, "Student > Master"=>4, "Other"=>15, "Student > Bachelor"=>2, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>1, "Professor"=>5}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Researcher"=>30, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>18, "Student > Postgraduate"=>2, "Student > Master"=>4, "Other"=>15, "Student > Bachelor"=>2, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>1, "Professor"=>5}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>16, "Agricultural and Biological Sciences"=>46, "Medicine and Dentistry"=>8, "Physics and Astronomy"=>1, "Social Sciences"=>1, "Computer Science"=>6, "Immunology and Microbiology"=>1, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>8}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>46}, "Computer Science"=>{"Computer Science"=>6}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>16}, "Unspecified"=>{"Unspecified"=>4}}, "reader_count_by_country"=>{"Sweden"=>2, "United States"=>2, "Brazil"=>1, "United Kingdom"=>4, "Italy"=>1, "Germany"=>1}, "group_count"=>4}

ORCID | Further Information

CrossRef

• http://doi.org/10.1089/dna.2017.3731
• http://doi.org/10.1371/journal.pone.0101154
• http://doi.org/10.1038/srep26732
• http://doi.org/10.1200/JCO.2014.59.1503
• http://doi.org/10.3233/BLC-150007
• http://doi.org/10.1182/blood-2012-12-471888
• http://doi.org/10.1111/cyt.12161
• http://doi.org/10.1038/srep03494
• http://doi.org/10.4161/onci.20730
• http://doi.org/10.1038/leu.2014.322
• http://doi.org/10.1186/s40164-016-0063-0
• http://doi.org/10.1182/blood-2018-08-872226
• http://doi.org/10.1111/odi.12246
• http://doi.org/10.1182/blood-2012-03-412981
• http://doi.org/10.1002/gcc.22077
• http://doi.org/10.1038/ncomms7997

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• 4081514
• 4321413
• 3861801
• 3429561

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/672386"], "description"=>"<p>The efficiency is shown as median depth of coverage of probe regions with different GC percentage. The GC percentage range of the probes is shown on the x axis. The median depth of coverage for the probes in the HapMap sample, either SA or MSA-Cap libraries, is represented on the left y axis. The percentage of probes in each GC content is shown on the right y axis.</p>", "links"=>[], "tags"=>["probes", "gc-content", "gc", "bases", "sa", "msa-cap", "hapmap"], "article_id"=>342860, "categories"=>["Cancer", "Biological Sciences", "Genetics", "Hematology"], "users"=>["Iwanka Kozarewa", "Juan Manuel Rosa-Rosa", "Christopher P. Wardell", "Brian A. Walker", "Kerry Fenwick", "Ioannis Assiotis", "Costas Mitsopoulos", "Marketa Zvelebil", "Gareth J. Morgan", "Alan Ashworth", "Christopher J."], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032617.g002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Capture_efficiency_of_probes_with_different_GC_content_percentage_of_GC_bases_from_the_total_bases_for_SA_and_MSA_Cap_HapMap_NA12813_libraries_/342860", "title"=>"Capture efficiency of probes with different GC-content (percentage of GC bases from the total bases) for SA and MSA-Cap HapMap (NA12813) libraries.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-03-05 00:47:40"}
• {"files"=>["https://ndownloader.figshare.com/files/344233", "https://ndownloader.figshare.com/files/344348", "https://ndownloader.figshare.com/files/344392", "https://ndownloader.figshare.com/files/344558"], "description"=>"<div><p>Next generation DNA sequencing (NGS) technologies have revolutionized the pace at which whole genome and exome sequences can be generated. However, despite these advances, many of the methods for targeted resequencing, such as the generation of high-depth exome sequences, are somewhat limited by the relatively large amounts of starting DNA that are normally required. In the case of tumour analysis this is particularly pertinent as many tumour biopsies often return submicrogram quantities of DNA, especially when tumours are microdissected prior to analysis. Here, we present a method for exome capture and resequencing using as little as 50 ng of starting DNA. The sequencing libraries generated by this minimal starting amount (MSA-Cap) method generate datasets that are comparable to standard amount (SA) whole exome libraries that use three micrograms of starting DNA. This method, which can be performed in most laboratories using commonly available reagents, has the potential to enhance large scale profiling efforts such as the resequencing of tumour exomes.</p> </div>", "links"=>[], "tags"=>["modified", "exome", "resequencing", "amounts", "dna"], "article_id"=>128040, "categories"=>["Cancer", "Biological Sciences", "Genetics", "Hematology"], "users"=>["Iwanka Kozarewa", "Juan Manuel Rosa-Rosa", "Christopher P. Wardell", "Brian A. Walker", "Kerry Fenwick", "Ioannis Assiotis", "Costas Mitsopoulos", "Marketa Zvelebil", "Gareth J. Morgan", "Alan Ashworth", "Christopher J."], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0032617.s001", "https://dx.doi.org/10.1371/journal.pone.0032617.s002", "https://dx.doi.org/10.1371/journal.pone.0032617.s003", "https://dx.doi.org/10.1371/journal.pone.0032617.s004"], "stats"=>{"downloads"=>10, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/A_Modified_Method_for_Whole_Exome_Resequencing_from_Minimal_Amounts_of_Starting_DNA/128040", "title"=>"A Modified Method for Whole Exome Resequencing from Minimal Amounts of Starting DNA", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-03-05 02:14:00"}
• {"files"=>["https://ndownloader.figshare.com/files/672707"], "description"=>"<p>For the PCL-tumour sample, the variants called by deep sequencing were compared to data from Affymetrix SNP 6.0 DNA array while for the HapMap sample published data were used for the comparison.</p>", "links"=>[], "tags"=>["concordance", "snp", "calls", "pcl-tumour", "hapmap"], "article_id"=>343188, "categories"=>["Cancer", "Biological Sciences", "Genetics", "Hematology"], "users"=>["Iwanka Kozarewa", "Juan Manuel Rosa-Rosa", "Christopher P. Wardell", "Brian A. Walker", "Kerry Fenwick", "Ioannis Assiotis", "Costas Mitsopoulos", "Marketa Zvelebil", "Gareth J. Morgan", "Alan Ashworth", "Christopher J."], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032617.t002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Genotype_concordance_for_SNP_calls_in_a_PCL_tumour_sample_and_a_HapMap_NA12813_sample_/343188", "title"=>"Genotype concordance for SNP calls in a PCL-tumour sample and a HapMap (NA12813) sample.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-03-05 00:53:08"}
• {"files"=>["https://ndownloader.figshare.com/files/672588"], "description"=>"<p>Chromosomes 1 to 22 plus X and Y are shown on the x axis. The log₂ ratio of the normalized by the normal depth values for the PCL-tumour libraries is represented on the y axis. Arrows point towards the detected by deep sequencing and previously identified by SNP6 array copy number changes: gain (6p), del (6q), del (12p), del (13q) and del (17p).</p>", "links"=>[], "tags"=>["profiles", "sequencing", "pcl-tumour", "prepared", "sa-", "msa-cap"], "article_id"=>343056, "categories"=>["Cancer", "Biological Sciences", "Genetics", "Hematology"], "users"=>["Iwanka Kozarewa", "Juan Manuel Rosa-Rosa", "Christopher P. Wardell", "Brian A. Walker", "Kerry Fenwick", "Ioannis Assiotis", "Costas Mitsopoulos", "Marketa Zvelebil", "Gareth J. Morgan", "Alan Ashworth", "Christopher J."], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032617.g004", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Copy_number_profiles_estimated_by_deep_sequencing_of_PCL_tumour_samples_prepared_using_the_SA_or_MSA_Cap_methods_/343056", "title"=>"Copy number profiles estimated by deep sequencing of PCL-tumour samples, prepared using the SA- or MSA-Cap methods.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-03-05 00:50:56"}
• {"files"=>["https://ndownloader.figshare.com/files/672477"], "description"=>"<p>Non-filtered variants were identified in each sample using Broad Institute Best Practice pipeline version 1.0.5273 upon comparison to human hg19 reference sequence and categorized according to putative gene effect. The cumulative number of variants for each library type is shown on the x axis and the sample and library type on the y axis. Variant categories, as assigned by the Ensembl database, are on the right side of the figure.</p>", "links"=>[], "tags"=>["sa", "msa-cap", "prepared", "pcl-tumour", "pcl-buccal", "swab"], "article_id"=>342952, "categories"=>["Cancer", "Biological Sciences", "Genetics", "Hematology"], "users"=>["Iwanka Kozarewa", "Juan Manuel Rosa-Rosa", "Christopher P. Wardell", "Brian A. Walker", "Kerry Fenwick", "Ioannis Assiotis", "Costas Mitsopoulos", "Marketa Zvelebil", "Gareth J. Morgan", "Alan Ashworth", "Christopher J."], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032617.g003", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mutational_spectrum_from_SA_and_MSA_Cap_libraries_prepared_from_PCL_tumour_or_PCL_buccal_swab_samples_/342952", "title"=>"Mutational spectrum from SA and MSA-Cap libraries, prepared from PCL-tumour or PCL-buccal swab samples.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-03-05 00:49:12"}
• {"files"=>["https://ndownloader.figshare.com/files/672289"], "description"=>"<p>Flow chart comparing the standard Agilent Whole Exome Target Enrichment protocol (SA protocol, v. 2.0.1), and the Minimal Starting Amount Capture (MSA-Cap) protocol.</p>", "links"=>[], "tags"=>["comparing", "agilent", "exome", "enrichment"], "article_id"=>342762, "categories"=>["Cancer", "Biological Sciences", "Genetics", "Hematology"], "users"=>["Iwanka Kozarewa", "Juan Manuel Rosa-Rosa", "Christopher P. Wardell", "Brian A. Walker", "Kerry Fenwick", "Ioannis Assiotis", "Costas Mitsopoulos", "Marketa Zvelebil", "Gareth J. Morgan", "Alan Ashworth", "Christopher J."], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032617.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flow_chart_comparing_the_standard_Agilent_Whole_Exome_Target_Enrichment_protocol_SA_protocol_v_2_0_1_and_the_Minimal_Starting_Amount_Capture_MSA_Cap_protocol_/342762", "title"=>"Flow chart comparing the standard Agilent Whole Exome Target Enrichment protocol (SA protocol, v. 2.0.1), and the Minimal Starting Amount Capture (MSA-Cap) protocol.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-03-05 00:46:02"}
• {"files"=>["https://ndownloader.figshare.com/files/672662"], "description"=>"<p>Target enrichment and sequencing quality metrics.</p>", "links"=>[], "tags"=>["enrichment", "sequencing"], "article_id"=>343141, "categories"=>["Cancer", "Biological Sciences", "Genetics", "Hematology"], "users"=>["Iwanka Kozarewa", "Juan Manuel Rosa-Rosa", "Christopher P. Wardell", "Brian A. Walker", "Kerry Fenwick", "Ioannis Assiotis", "Costas Mitsopoulos", "Marketa Zvelebil", "Gareth J. Morgan", "Alan Ashworth", "Christopher J."], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032617.t001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Target_enrichment_and_sequencing_quality_metrics_/343141", "title"=>"Target enrichment and sequencing quality metrics.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-03-05 00:52:21"}

PMC Usage Stats | Further Information

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Relative Metric

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F1000Prime