In this figure we show the output of the half-loop biclustering algorithm applied to the BDRN cohort in arm-1 (limited to those SNPs with maf ≥0.25).
<p>As described in the main text, the algorithm proceeds iteratively, eliminating rows and columns from the case-subject-array <i>D</i> until all have been removed. At each iteration <i>i</i>, the remaining submatrix <i>D</i>(<i>i</i>) comprises...
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2025
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| _version_ | 1852023186431934464 |
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| author | Caroline C. McGrouther (5216153) |
| author2 | Aaditya V. Rangan (14659986) Arianna Di Florio (20636356) Jeremy A. Elman (9602147) Nicholas J. Schork (176346) John Kelsoe (3437189) |
| author2_role | author author author author author |
| author_facet | Caroline C. McGrouther (5216153) Aaditya V. Rangan (14659986) Arianna Di Florio (20636356) Jeremy A. Elman (9602147) Nicholas J. Schork (176346) John Kelsoe (3437189) |
| author_role | author |
| dc.creator.none.fl_str_mv | Caroline C. McGrouther (5216153) Aaditya V. Rangan (14659986) Arianna Di Florio (20636356) Jeremy A. Elman (9602147) Nicholas J. Schork (176346) John Kelsoe (3437189) |
| dc.date.none.fl_str_mv | 2025-01-29T18:23:47Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0314288.g002 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/In_this_figure_we_show_the_output_of_the_half-loop_biclustering_algorithm_applied_to_the_BDRN_cohort_in_arm-1_limited_to_those_SNPs_with_maf_0_25_/28304632 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Genetics Neuroscience Pharmacology Biotechnology Evolutionary Biology Marine Biology Mental Health Infectious Diseases Plant Biology Biological Sciences not elsewhere classified termed &# 8216 psychiatric genomics consortium leverage recent advances e ., biclusters corrected biclustering algorithm subgroup may represent subgroup &# 8217 pgc containing 5781 various bd studies bd subtype information improve risk prediction specific pattern highlighted homogeneous genetic subgroup relatively small subset genetically homogeneous subtype discovered without using bicluster &# 8217 specific genetic pattern correlated genetic risk 2524 bd cases genetic heterogeneity delineating disorder </ p specific pattern genetic subgroup bd cases genetic level genetic data pgc ). 9752 cases bipolar disorder xlink "> successfully identified subphenotypic data subjects define set aside remaining data related signal prs ), primary focus particularly notable one way informed polygenic gwas analyses fully understood first apply expression across eliminate noise driven subgroups challenging task broad phenotype |
| dc.title.none.fl_str_mv | In this figure we show the output of the half-loop biclustering algorithm applied to the BDRN cohort in arm-1 (limited to those SNPs with maf ≥0.25). |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>As described in the main text, the algorithm proceeds iteratively, eliminating rows and columns from the case-subject-array <i>D</i> until all have been removed. At each iteration <i>i</i>, the remaining submatrix <i>D</i>(<i>i</i>) comprises case-subjects and allele-combinations . At each iteration we record the ‘row-trace’ , which is the covariate-corrected average level of differential-expression between <i>D</i>(<i>i</i>) and the control-subjects <i>X</i>. In the top row of subplots we show the row-trace for the data (red) as well as for 128 label-shuffled trials (black). Each of the row-traces has been transformed into an iteration-dependent z-score (estimated using the distribution of label-shuffled trials at that iteration). In the bottom row we show the corresponding empirical p-value, as estimated for each iteration using the label-shuffled trials. The dashed black-line corresponds to the 95th percentile (i.e., a significance value of 0.05 if each iteration were considered independently). If the signal were homogeneous we would expect to see the red trace begin at a high value and decay relatively monotonically. By contrast, we see strong evidence for heterogeneity; the red trace is far from monotonic. The overall p-value for the data (red-trace), estimated using the strategy in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0314288#pone.0314288.ref064" target="_blank">64</a>], is <i>p</i> ≲ 1/64. Note that the trace is significant over a range of iterations, including <i>i</i> ∈ [175, 350].</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_2aff7a3bc66980a01cec0b6b8e26f2ef |
| identifier_str_mv | 10.1371/journal.pone.0314288.g002 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28304632 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | In this figure we show the output of the half-loop biclustering algorithm applied to the BDRN cohort in arm-1 (limited to those SNPs with maf ≥0.25).Caroline C. McGrouther (5216153)Aaditya V. Rangan (14659986)Arianna Di Florio (20636356)Jeremy A. Elman (9602147)Nicholas J. Schork (176346)John Kelsoe (3437189)GeneticsNeurosciencePharmacologyBiotechnologyEvolutionary BiologyMarine BiologyMental HealthInfectious DiseasesPlant BiologyBiological Sciences not elsewhere classifiedtermed &# 8216psychiatric genomics consortiumleverage recent advancese ., biclusterscorrected biclustering algorithmsubgroup may representsubgroup &# 8217pgc containing 5781various bd studiesbd subtype informationimprove risk predictionspecific pattern highlightedhomogeneous genetic subgrouprelatively small subsetgenetically homogeneous subtypediscovered without usingbicluster &# 8217specific genetic patterncorrelated genetic risk2524 bd casesgenetic heterogeneity delineatingdisorder </ pspecific patterngenetic subgroupbd casesgenetic levelgenetic datapgc ).9752 casesbipolar disorderxlink ">successfully identifiedsubphenotypic datasubjects defineset asideremaining datarelated signalprs ),primary focusparticularly notableone wayinformed polygenicgwas analysesfully understoodfirst applyexpression acrosseliminate noisedriven subgroupschallenging taskbroad phenotype<p>As described in the main text, the algorithm proceeds iteratively, eliminating rows and columns from the case-subject-array <i>D</i> until all have been removed. At each iteration <i>i</i>, the remaining submatrix <i>D</i>(<i>i</i>) comprises case-subjects and allele-combinations . At each iteration we record the ‘row-trace’ , which is the covariate-corrected average level of differential-expression between <i>D</i>(<i>i</i>) and the control-subjects <i>X</i>. In the top row of subplots we show the row-trace for the data (red) as well as for 128 label-shuffled trials (black). Each of the row-traces has been transformed into an iteration-dependent z-score (estimated using the distribution of label-shuffled trials at that iteration). In the bottom row we show the corresponding empirical p-value, as estimated for each iteration using the label-shuffled trials. The dashed black-line corresponds to the 95th percentile (i.e., a significance value of 0.05 if each iteration were considered independently). If the signal were homogeneous we would expect to see the red trace begin at a high value and decay relatively monotonically. By contrast, we see strong evidence for heterogeneity; the red trace is far from monotonic. The overall p-value for the data (red-trace), estimated using the strategy in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0314288#pone.0314288.ref064" target="_blank">64</a>], is <i>p</i> ≲ 1/64. Note that the trace is significant over a range of iterations, including <i>i</i> ∈ [175, 350].</p>2025-01-29T18:23:47ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0314288.g002https://figshare.com/articles/figure/In_this_figure_we_show_the_output_of_the_half-loop_biclustering_algorithm_applied_to_the_BDRN_cohort_in_arm-1_limited_to_those_SNPs_with_maf_0_25_/28304632CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/283046322025-01-29T18:23:47Z |
| spellingShingle | In this figure we show the output of the half-loop biclustering algorithm applied to the BDRN cohort in arm-1 (limited to those SNPs with maf ≥0.25). Caroline C. McGrouther (5216153) Genetics Neuroscience Pharmacology Biotechnology Evolutionary Biology Marine Biology Mental Health Infectious Diseases Plant Biology Biological Sciences not elsewhere classified termed &# 8216 psychiatric genomics consortium leverage recent advances e ., biclusters corrected biclustering algorithm subgroup may represent subgroup &# 8217 pgc containing 5781 various bd studies bd subtype information improve risk prediction specific pattern highlighted homogeneous genetic subgroup relatively small subset genetically homogeneous subtype discovered without using bicluster &# 8217 specific genetic pattern correlated genetic risk 2524 bd cases genetic heterogeneity delineating disorder </ p specific pattern genetic subgroup bd cases genetic level genetic data pgc ). 9752 cases bipolar disorder xlink "> successfully identified subphenotypic data subjects define set aside remaining data related signal prs ), primary focus particularly notable one way informed polygenic gwas analyses fully understood first apply expression across eliminate noise driven subgroups challenging task broad phenotype |
| status_str | publishedVersion |
| title | In this figure we show the output of the half-loop biclustering algorithm applied to the BDRN cohort in arm-1 (limited to those SNPs with maf ≥0.25). |
| title_full | In this figure we show the output of the half-loop biclustering algorithm applied to the BDRN cohort in arm-1 (limited to those SNPs with maf ≥0.25). |
| title_fullStr | In this figure we show the output of the half-loop biclustering algorithm applied to the BDRN cohort in arm-1 (limited to those SNPs with maf ≥0.25). |
| title_full_unstemmed | In this figure we show the output of the half-loop biclustering algorithm applied to the BDRN cohort in arm-1 (limited to those SNPs with maf ≥0.25). |
| title_short | In this figure we show the output of the half-loop biclustering algorithm applied to the BDRN cohort in arm-1 (limited to those SNPs with maf ≥0.25). |
| title_sort | In this figure we show the output of the half-loop biclustering algorithm applied to the BDRN cohort in arm-1 (limited to those SNPs with maf ≥0.25). |
| topic | Genetics Neuroscience Pharmacology Biotechnology Evolutionary Biology Marine Biology Mental Health Infectious Diseases Plant Biology Biological Sciences not elsewhere classified termed &# 8216 psychiatric genomics consortium leverage recent advances e ., biclusters corrected biclustering algorithm subgroup may represent subgroup &# 8217 pgc containing 5781 various bd studies bd subtype information improve risk prediction specific pattern highlighted homogeneous genetic subgroup relatively small subset genetically homogeneous subtype discovered without using bicluster &# 8217 specific genetic pattern correlated genetic risk 2524 bd cases genetic heterogeneity delineating disorder </ p specific pattern genetic subgroup bd cases genetic level genetic data pgc ). 9752 cases bipolar disorder xlink "> successfully identified subphenotypic data subjects define set aside remaining data related signal prs ), primary focus particularly notable one way informed polygenic gwas analyses fully understood first apply expression across eliminate noise driven subgroups challenging task broad phenotype |