scGAD: Performing scGAD for each single-cell data
In sshen82/BandNorm: BandNorm Method for single-cell Hi-C

scGAD

R Documentation

Performing scGAD for each single-cell data

This function allows you to calculate GAD value for each gene in each cell.

scGAD(
  path = NULL,
  hic_df = NULL,
  genes,
  depthNorm = TRUE,
  cores = 4,
  threads = 8,
  binPair = TRUE,
  format = "short",
  res = 10000
)

`path`	A path to the single-cell Hi-C data. The data format should be the same as in the bandnorm hic_df input.
`hic_df`	You can also load dataframe containing all Hi-C data to here, but it is not recommended, since in scGAD, we are dealing with high resolution matrices, and it will consume a lot of memory if we load it directly.
`genes`	A data frame containing 5 columns: chrmomsome, start, end, strand, gene name.
`depthNorm`	Whether to normalize the sequencing depth effect. Default is TRUE.
`cores`	Number of cores used for parallel running. Default is 4.
`threads`	Number of threads for fread function, default is 8.
`binPair`	Use bin pair or valid reads. The former is faster since it is already binned, but the latter will be more accurate. Default is TRUE.
`format`	The format of the valid pairs. "short", "medium", "long", "4DN" are supported. See https://github.com/aidenlab/juicer/wiki/Pre.
`res`	The resolution of the data. Used only when binPair = TRUE. Default is 10000.