Supported Format

• Pre-processed Matrices: If the data is already processed into matrices for intra-chromosomal contacts, the chromosome from the same cell must be stored in the same folder with chromosome names as file names (e.g., scHiC/cell_1/chr1.txt). You only need to provide the folder name for a cell (e.g., scHiC/cell_1).

  • npy: numpy.array / numpy.matrix
  • npz: scipy.sparse.coo_matrix
  • matrix: matrix stored as pure text
  • matrix_txt: matrix stored as .txt file
  • HiCRep: the format required by HiCRep package

• Edge List
  For all formats below:
    str - strand (forward / reverse)
    chr - chromosome
    pos - position
    score - contact reads
    frag - fragments (will be ignored)
    mapq - map quality
  

  • Shortest

  <chr1> <pos1> <chr2> <pos2>
  

  • Shortest_Score

  <chr1> <pos1> <chr2> <pos2> <score>
  

  • Short

  <str1> <chr1> <pos1> <frag1> <str2> <chr2> <pos2> <frag2>
  

  • Short_Score

  <str1> <chr1> <pos1> <frag1> <str2> <chr2> <pos2> <frag2> <score>
  

  • Medium

  <readname> <str1> <chr1> <pos1> <frag1> <str2> <chr2> <pos2> <frag2> <mapq1> <mapq2>
  

  • Long

  <str1> <chr1> <pos1> <frag1> <str2> <chr2> <pos2> <frag2> <mapq1> <cigar1> <sequence1> <mapq2> <cigar2> <sequence2> <readname1> <readname2>
  

  • 4DN

  ## pairs format v1.0
  #columns: readID chr1 position1 chr2 position2 strand1 strand2
  

• .hic format: we adapted “straw” from JuiceTools.

• .mcool format: we adapted “dump” from cool.

• Other formats: simply give the indices (start from 1) in the order of
  “chromosome1 - position1 - chromosome2 - position2 - score” or
  “chromosome1 - position1 - chromosome2 - position2” or
  “chromosome1 - position1 - chromosome2 - position2 - mapq1 - mapq2”.
  For example, you can provide “2356” or [2, 3, 5, 6] if the file takes this format:

<name> <chromosome1> <position1> <frag1> <chromosome2> <position2> <frag2> <strand1> <strand2>
contact_1 chr1 3000000 1 chr1 3001000 1 + -