ArticlebioRxiv : the preprint server for biology2025
POPARI: Modeling multisample variation in spatial transcriptomics.
Shahul Alam, Tianming Zhou, Ellie Haber, Benjamin Chidester, Sophia Liu, Fei Chen, Jian Ma
Abstract readPreprint
In one paragraphArticle in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
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0citing papers in PubMed
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What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
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4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
7 authors.
Shahul AlamRay and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Tianming ZhouRay and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Ellie HaberMachine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Benjamin ChidesterRay and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Sophia LiuBiophysics Program, Harvard University, Boston, MA 02115, USA.
Jian MaRay and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.ORCID 0000-0002-4202-5834 Funding
Multiscale Analyses of 4D Nucleome Structure and Function by Comprehensive Multimodal Data IntegrationUM1HG011593 · NHGRI · CARNEGIE-MELLON UNIVERSITY · PI ALBER, FRANK, BELMONT, ANDREW STEVEN · 2020 to 2024
$10.4MWashU-Northwestern Genomic Variation and Function Data and Administrative Coordinating CenterU24HG012070 · NHGRI · WASHINGTON UNIVERSITY · PI Ting Wang, Feng Yue · 2021 to 2026
$9.7MIntegrated Interdisciplinary, inter-university PhD Program Computational Biology (T32)T32EB009403 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BAHAR, IVET, BAR-JOSEPH, ZIV · 2009 to 2023
$4.4MComputational Methods for Next-Generation Comparative GenomicsR01HG007352 · NHGRI · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI MA, JIAN · 2014 to 2023
$2.8MComputational methods for studying single-cell 3D genomeR01HG012303 · NHGRI · CARNEGIE-MELLON UNIVERSITY · PI DUAN, ZHIJUN, MA, JIAN · 2022 to 2025
$2.2MSpatial omics technologies to map the senescent cell microenvironmentUH3CA268202 · NCI · BROWN UNIVERSITY · PI MA, JIAN, NERETTI, NICOLA · 2023 to 2025
$2.2MSpatial omics technologies to map the senescent cell microenvironmentUG3CA268202 · NCI · BROWN UNIVERSITY · PI MA, JIAN, NERETTI, NICOLA · 2021 to 2022
$916kThree-dimensional mapping and modeling of combinatorial interactions underlying biomolecular condensates in olfactory neuronsR21DA061481 · NIDA · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI GUTTMAN, MITCHELL, LOMVARDAS, STAVROS · 2024 to 2025
$465kNCI NIH HHS UG3 CA268202NCI NIH HHS UH3 CA268202NHGRI NIH HHS R01 HG007352NHGRI NIH HHS R01 HG012303NHGRI NIH HHS U24 HG012070NHGRI NIH HHS UM1 HG011593NIBIB NIH HHS T32 EB009403NIDA NIH HHS R21 DA061481
6 · The paper itselfAbstract
Integrating spatially-resolved transcriptomics (SRT) across biological samples is essential for understanding dynamic changes in tissue architecture and cell-cell interactions
Identifiers
PMID40462963
PMCPMC12132593
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