Detection of Simultaneous Group Effects in MicroRNA Expression and Related Target Gene Sets
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{"title"=>"Detection of simultaneous group effects in microRNA expression and related target gene sets", "type"=>"journal", "authors"=>[{"first_name"=>"Stephan", "last_name"=>"Artmann", "scopus_author_id"=>"55256727200"}, {"first_name"=>"Klaus", "last_name"=>"Jung", "scopus_author_id"=>"56728979300"}, {"first_name"=>"Annalen", "last_name"=>"Bleckmann", "scopus_author_id"=>"16303183500"}, {"first_name"=>"Tim", "last_name"=>"Beißbarth", "scopus_author_id"=>"16174223900"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"22723856", "doi"=>"10.1371/journal.pone.0038365", "pui"=>"365049407", "issn"=>"19326203", "sgr"=>"84862562497", "scopus"=>"2-s2.0-84862562497"}, "id"=>"85105b5e-b762-3998-a24b-e05b4a64f76c", "abstract"=>"Expression levels of mRNAs are among other factors regulated by microRNAs. A particular microRNA can bind specifically to several target mRNAs and lead to their degradation. Expression levels of both, mRNAs and microRNAs, can be obtained by microarray experiments. In order to increase the power of detecting microRNAs that are differentially expressed between two different groups of samples, we incorporate expression levels of their related target gene sets. Group effects are determined individually for each microRNA, and by enrichment tests and global tests for target gene sets. The resulting lists of p-values from individual and set-wise testing are combined by means of meta analysis. We propose a new approach to connect microRNA-wise and gene set-wise information by means of p-value combination as often used in meta-analysis. In this context, we evaluate the usefulness of different approaches of gene set tests. In a simulation study we reveal that our combination approach is more powerful than microRNA-wise testing alone. Furthermore, we show that combining microRNA-wise results with 'competitive' gene set tests maintains a pre-specified false discovery rate. In contrast, a combination with 'self-contained' gene set tests can harm the false discovery rate, particularly when gene sets are not disjunct.", "link"=>"http://www.mendeley.com/research/detection-simultaneous-group-effects-microrna-expression-related-target-gene-sets", "reader_count"=>10, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>2, "Researcher"=>1, "Student > Ph. D. Student"=>2, "Student > Master"=>4, "Student > Bachelor"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>2, "Researcher"=>1, "Student > Ph. D. Student"=>2, "Student > Master"=>4, "Student > Bachelor"=>1}, "reader_count_by_subject_area"=>{"Biochemistry, Genetics and Molecular Biology"=>3, "Agricultural and Biological Sciences"=>5, "Medicine and Dentistry"=>1, "Psychology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Psychology"=>{"Psychology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>5}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}}, "reader_count_by_country"=>{"United States"=>1, "Brazil"=>1}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/621806"], "description"=>"<p>The top-scoring Gene Ontology (GO) terms with lowest p-values (according to one-sided Fisher’s exact test) of miRNAs’ target sets from Neurogenesis (above) and HIV (below) data example.</p>", "links"=>[], "tags"=>["genetics and genomics", "oncology", "Biochemistry", "mathematics"], "article_id"=>292301, "categories"=>["Cancer", "Mathematics", "Biochemistry", "Genetics"], "users"=>["Stephan Artmann", "Klaus Jung", "Annalen Bleckmann", "Tim Beißbarth"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0038365.t006", "stats"=>{"downloads"=>2, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_GO_Terms_for_Data_Examples_/292301", "title"=>"GO-Terms for Data Examples.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:42:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/621507"], "description"=>"<p>Effects are presented for component-wise testing (dotted line), target set-wise testing (dashed line) and the combination approach (solid line). While the competitive approaches such as the ‘Wilcoxon’-based gene set test (top) still maintained the pre-specified -level of 5 when target gene sets overlapped, the increased dramatically when employing the self-contained approaches such as the ‘globaltest’ procedure (bottom).</p>", "links"=>[], "tags"=>["overlapping", "sets", "simulated"], "article_id"=>291998, "categories"=>["Cancer", "Mathematics", "Biochemistry", "Genetics"], "users"=>["Stephan Artmann", "Klaus Jung", "Annalen Bleckmann", "Tim Beißbarth"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0038365.g002", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effect_of_overlapping_target_gene_sets_on_the_simulated_/291998", "title"=>"Effect of overlapping target gene sets on the simulated .", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 03:41:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/621895"], "description"=>"<p>Simulated with respect to the type of gene set test and covariance matrix using the approach of combined target set and microRNA-wise testing. Results are presented for the simulation setting of overlapping and disjunct target sets. Presented numbers are the minimum, median and maximum simulated across the range of the log fold change (between 0 and 6). Rates larger than the pre-specified level of 0.05 are printed in bold.</p>", "links"=>[], "tags"=>["microrna-selection", "microrna-wise"], "article_id"=>292387, "categories"=>["Cancer", "Mathematics", "Biochemistry", "Genetics"], "users"=>["Stephan Artmann", "Klaus Jung", "Annalen Bleckmann", "Tim Beißbarth"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0038365.t002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulated_for_microRNA_selection_based_on_combined_target_set_and_microRNA_wise_testing_/292387", "title"=>"Simulated for microRNA-selection based on combined target set and microRNA-wise testing.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:43:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/621424"], "description"=>"<p>The links between microRNAs and their target mRNAs are taken from public databases. MicroRNAs and target sets are first analysed separately and obtained <i>p</i>-values are combined as final result.</p>", "links"=>[], "tags"=>["combining", "levels", "mirnas"], "article_id"=>291912, "categories"=>["Cancer", "Mathematics", "Biochemistry", "Genetics"], "users"=>["Stephan Artmann", "Klaus Jung", "Annalen Bleckmann", "Tim Beißbarth"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0038365.g001", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flow_chart_of_combining_expression_levels_of_miRNAs_and_their_related_target_mRNAs_/291912", "title"=>"Flow chart of combining expression levels of miRNAs and their related target mRNAs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 03:40:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/621667"], "description"=>"<p>Left: component-wise testing (dotted line), target testing with ‘ROAST’ (dashed line) and the combination approach (solid line), each in the case of an autoregressive covariance structure and non-overlapping target sets. Right: combination approach based on ‘globaltest’ (dotted line), ‘Wilcoxon’ (dashed line) and ‘Romer’ (solid line), each in the case of an unstructured covariance matrix and overlapping target sets.</p>", "links"=>[], "tags"=>["rates"], "article_id"=>292163, "categories"=>["Cancer", "Mathematics", "Biochemistry", "Genetics"], "users"=>["Stephan Artmann", "Klaus Jung", "Annalen Bleckmann", "Tim Beißbarth"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0038365.g003", "stats"=>{"downloads"=>2, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulated_average_power_rates_with_respect_to_the_log_fold_change_/292163", "title"=>"Simulated average power rates with respect to the log fold change .", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 03:41:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/621842"], "description"=>"<p>Simulated with respect to the type of gene set test and covariance matrix using the approach of selecting microRNAs by testing their target gene sets. Results are presented for the simulation setting of overlapping and disjunct target sets. Presented numbers are the minimum, median and maximum simulated across the range of the log fold change (between 0 and 6). Rates larger than the pre-specified level of 0.05 are printed in bold.</p>", "links"=>[], "tags"=>["microrna-selection"], "article_id"=>292337, "categories"=>["Cancer", "Mathematics", "Biochemistry", "Genetics"], "users"=>["Stephan Artmann", "Klaus Jung", "Annalen Bleckmann", "Tim Beißbarth"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0038365.t001", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulated_for_microRNA_selection_based_on_target_set_testing_/292337", "title"=>"Simulated for microRNA-selection based on target set testing.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:42:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/621778"], "description"=>"<p>Rating orders are based on the following gene set tests: GlobalTest (GT), GlobalAncova (GA), RepeatedHighDim (RHD), Kolm. Smirnov (KS), Wilcoxon (W), Fisher (F), ROAST (Ro) and Romer (R). The rank 1 denotes the largest power rate while the rank 8 denotes the worst power rate (comparable -curves were given the same position in the ranking). Note that W and KS always have the largest power rates.</p>", "links"=>[], "tags"=>["orders", "simulations"], "article_id"=>292271, "categories"=>["Cancer", "Mathematics", "Biochemistry", "Genetics"], "users"=>["Stephan Artmann", "Klaus Jung", "Annalen Bleckmann", "Tim Beißbarth"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0038365.t004", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Rating_orders_of_the_in_simulations_of_combined_testing_/292271", "title"=>"Rating orders of the in simulations of combined testing.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:42:30"}
  • {"files"=>["https://ndownloader.figshare.com/files/621754"], "description"=>"<p>MicroRNAs originally detected in expression data from rat brains by Nielsen <i>et al.</i><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038365#pone.0038365-Nielsen1\" target=\"_blank\">[28]</a>. Columns from left to right are the name of the microRNAs, the originally reported results (columns 2-4) and the results of our re-analysis (columns 5-7). Nielsen <i>et al.</i> performed their gene set tests separately for subsets of up- and down-regulated mRNAs yielding two results per gene set. Our re-analysis was performed by use of the combination approach based on either global tests, enrichment tests or rotation tests (‘ROAST’ (R), ‘Romer’ (r)). Significance (sig.) was declared when the FDR-adjusted -value was and not significant (n. s.) otherwise.</p>", "links"=>[], "tags"=>["re-analysis", "micrornas"], "article_id"=>292247, "categories"=>["Cancer", "Mathematics", "Biochemistry", "Genetics"], "users"=>["Stephan Artmann", "Klaus Jung", "Annalen Bleckmann", "Tim Beißbarth"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0038365.t005", "stats"=>{"downloads"=>1, "page_views"=>36, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Original_results_and_re_analysis_of_microRNAs_in_rat_brains_/292247", "title"=>"Original results and re-analysis of microRNAs in rat brains.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:42:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/621866"], "description"=>"<p>Relation between simulated power rate curves of microRNA-wise, target set-wise and combined testing. Although, power curves sometimes intersected, this table gives the general tendency of the relations between the three approaches. *Compare <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038365#pone-0038365-g003\" target=\"_blank\">Figure 3</a> left.</p>", "links"=>[], "tags"=>["simulated"], "article_id"=>292357, "categories"=>["Cancer", "Mathematics", "Biochemistry", "Genetics"], "users"=>["Stephan Artmann", "Klaus Jung", "Annalen Bleckmann", "Tim Beißbarth"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0038365.t003", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Relation_between_simulated_power_rate_curves_/292357", "title"=>"Relation between simulated power rate curves.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:43:00"}

PMC Usage Stats | Further Information

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Relative Metric

{"start_date"=>"2012-01-01T00:00:00Z", "end_date"=>"2012-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[322, 550, 671, 773, 864, 955, 1048, 1135, 1223, 1308, 1387, 1465, 1534, 1602, 1673, 1744, 1813, 1885, 1955, 2026, 2093, 2160, 2228, 2290, 2349]}, {"subject_area"=>"/Biology and life sciences/Biochemistry", "average_usage"=>[316, 541, 663, 766, 856, 950, 1041, 1128, 1218, 1302, 1382, 1456, 1526, 1593, 1657, 1729, 1796, 1862, 1930, 1999, 2065, 2132, 2202, 2261, 2319]}, {"subject_area"=>"/Physical sciences/Mathematics", "average_usage"=>[325, 522, 627, 718, 804, 884, 969, 1052, 1131, 1207, 1277, 1346, 1415, 1478, 1542, 1605, 1663, 1723, 1776, 1839, 1895, 1955, 2008, 2066, 2123]}]}
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