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  "_id": "6ad1d67d0edca5be2502225d",
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  "Date": "2026-03-15",
  "Title": "Clustering Deviation Index (CDI)",
  "Description": "Single-cell RNA-sequencing (scRNA-seq) is widely used to\nexplore cellular variation. The analysis of scRNA-seq data\noften starts from clustering cells into subpopulations. This\ninitial step has a high impact on downstream analyses, and\nhence it is important to be accurate. However, there have not\nbeen unsupervised metric designed for scRNA-seq to evaluate\nclustering performance. Hence, we propose clustering deviation\nindex (CDI), an unsupervised metric based on the modeling of\nscRNA-seq UMI counts to evaluate clustering of cells.",
  "Authors@R": "c(person(\"Jiyuan\", \"Fang\", email = \"jfanglovestats@gmail.com\", role = c(\"cre\", \"aut\"), comment=c(ORCID=\"0000-0002-5004-4138\")), \nperson(\"Jichun\", \"Xie\", email = \"jichun.xie@duke.edu\", role = c(\"ctb\")),\nperson(\"Cliburn\", \"Chan\", email = \"cliburn.chan@duke.edu\", role = c(\"ctb\")),\nperson(\"Kouros\", \"Owzar\", email = \"kouros.owzar@duke.edu\", role = c(\"ctb\")),\nperson(\"Liuyang\", \"Wang\", email = \"liuyang.wang@duke.edu\", role = c(\"ctb\")),\nperson(\"Diyuan\", \"Qin\", email = \"diyuan.qin@duke.edu\", role = c(\"ctb\")),\nperson(\"Qi-Jing\", \"Li\", email = \"qi-jing.li@duke.edu\", role = c(\"ctb\")))",
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  "URL": "https://github.com/jichunxie/CDI",
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  "Date/Publication": "2026-04-28 13:01:09 UTC",
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