[
  {
    "author": [
      {
        "given": ["Jakob", "P"],
        "family": "Pettersen",
        "role": {},
        "email": {},
        "comment": {}
      },
      {
        "given": "Eivind",
        "family": "Almaas",
        "role": {},
        "email": {},
        "comment": {}
      }
    ],
    "title": "csdR, an R package for differential co-expression analysis",
    "journal": "BMC Bioinformatics",
    "year": "2022",
    "month": "Feb",
    "day": "19",
    "volume": "23",
    "number": "1",
    "pages": "79",
    "abstract": "Differential co-expression network analysis has become an important tool to gain understanding of biological phenotypes and diseases. The CSD algorithm is a method to generate differential co-expression networks by comparing gene co-expressions from two different conditions. Each of the gene pairs is assigned conserved (C), specific (S) and differentiated (D) scores based on the co-expression of the gene pair between the two conditions. The result of the procedure is a network where the nodes are genes and the links are the gene pairs with the highest C-, S-, and D-scores. However, the existing CSD-implementations suffer from poor computational performance, difficult user procedures and lack of documentation.",
    "issn": "1471-2105",
    "doi": "10.1186/s12859-022-04605-1",
    "url": "https://doi.org/10.1186/s12859-022-04605-1"
  }
]