{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T10:12:05Z","timestamp":1792663925319,"version":"4.5.0"},"posted":{"date-parts":[[2026,6,29]]},"group-title":"Bioinformatics","reference-count":29,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T00:00:00Z","timestamp":1782691200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006093","name":"Patient-Centered Outcomes Research Institute","doi-asserted-by":"crossref","award":["ME-2023C1-32148"],"award-info":[{"award-number":["ME-2023C1-32148"]}],"id":[{"id":"10.13039\/100006093","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000051","name":"National Human Genome Research Institute","doi-asserted-by":"crossref","award":["R00 HG011367"],"award-info":[{"award-number":["R00 HG011367"]}],"id":[{"id":"10.13039\/100000051","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Edge Foundation","award":["Karen EDGE Fellowship"],"award-info":[{"award-number":["Karen EDGE Fellowship"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,6,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Correlation is the dominant input to co-expression module discovery and miRNA-target inference. Both rely on an implicit assumption: a Pearson coefficient pooled across heterogeneous samples, whether tissues, cancer types, or cell types, estimates one biologically meaningful quantity. Simpson\u2019s paradox makes this assumption fragile in principle, since between- group mean shifts can dominate or reverse within-group associations. How often this happens in real transcriptomic data has not been quantified.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    Across 8,890 TCGA tumors from 31 cancer cohorts and 23,170,038 miRNA\u2013mRNA pairs, 94.8% of pairs showed both positive and negative within-cohort correlations. Restricting to the high-variance domain of one million pairs, 13.3% of pooled correlations with |\n                    <jats:italic>r<\/jats:italic>\n                    <jats:sub>global<\/jats:sub>\n                    |\u22650.2 reversed against the within-cohort majority at sign tolerance\n                    <jats:italic>\u03b5<\/jats:italic>\n                    = 0.05. Heterogeneity was the rule rather than the exception (median\n                    <jats:italic>I<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    = 0.86, IQR 0.80\u20130.90), and 99.5% of pairs rejected equal correlation across cohorts at FDR\n                    <jats:italic>&lt;<\/jats:italic>\n                    0.05. Of 692,770 experimentally validated miRTarBase v10 targets measurable in our data, only 0.9% were uniformly negative across cohorts. The pattern recurred across modalities. In GTEx, 21.0% of pooled signs disagreed with the tissue majority, and 23.5% of pairs flipped sign after tissue-mean removal. In 10x PBMC scRNA-seq, 13.1% of gene\u2013gene correlations flipped after cell-type-mean removal; in CITE-seq, 37.9% of protein\u2013RNA pairs flipped under a joint WNN partition of cells. Refining context reduced reversal, though by how much depended on the partition: within BRCA, 5.5% of pairs reversed under molecular PAM50 subtypes versus 0.35% under clinical IHC receptor status, and refining T cells into transcriptome-defined subtypes cut PBMC reversal from 11.8% to 0.13%.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>A single pooled correlation coefficient can invert direction relative to its within-context constituents at rates that are not negligible. Correlations should be reported with their context: the within-context distribution, a heterogeneity statistic, and a diagnostic that separates between-context mean shifts from within-context association. We provide a small R interface that computes these summaries.<\/jats:p>\n                <\/jats:sec>","DOI":"10.64898\/2026.06.23.733936","type":"posted-content","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T20:15:21Z","timestamp":1782764121000},"source":"Crossref","is-referenced-by-count":1,"title":["Context-dependent correlations mislead transcriptomic network inference in bulk and single-cell data"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5317-9820","authenticated-orcid":false,"given":"Amir","family":"Asiaee","sequence":"first","affiliation":[{"name":"Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Polina","family":"Bombina","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Data Science, and Epidemiology, Georgia Cancer Center at Augusta University, Augusta, GA 30912, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"suffix":"II","given":"Reginald L.","family":"McGee","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, Haverford College, Haverford, PA 19041, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jake","family":"Reed","sequence":"additional","affiliation":[{"name":"Department of Oncological Sciences, Huntsman Cancer Institute, Salt Lake City, UT 84112, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zachary B.","family":"Abrams","sequence":"additional","affiliation":[{"name":"Institute for Informatics, Data Science & Biostatistics, Washington University, St. Louis, MO 63110, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lynne V.","family":"Abruzzo","sequence":"additional","affiliation":[{"name":"Department of Pathology, Medical University of South Carolina, Charleston, SC 29425, United 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