cmstats module¶
cmstats.correlateCMaps(ccMapObjOne, ccMapObjTwo) |
To calculate correlation between two Hi-C maps |
cmstats.getAvgContactByDistance(ccmaps[, stats]) |
To calcualte average contact as a function of distance |
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correlateCMaps(ccMapObjOne, ccMapObjTwo, ignore_triangular=True, diagonal_offset=1, corrType='pearson', blockSize=None, slideStepSize=1, cutoffPercentile=None, workDir=None, outFile=None, logHandler=None)¶ To calculate correlation between two Hi-C maps
This function can be used to calculate either Pearson or Spearman rank-order correlation between two Hi-C maps. It also ignore lower-trangular matrix with diagnonal offset to avoid duplicate and large values.
Parameters: - ccMapObjOne (
gcMapExplorer.lib.ccmap.CCMAP) – FirstgcMapExplorer.lib.ccmap.CCMAPinstance containing Hi-C data - ccMapObjTwo (
gcMapExplorer.lib.ccmap.CCMAP) – SecondgcMapExplorer.lib.ccmap.CCMAPinstance containing Hi-C data - ignore_triangular (bool) – Whether entire matrix is considered or only one half triangular region of matrixis considered.
- diagonal_offset (int) – If
ignore_triangular=True, it is used to determine how much bins are ignored from the diagonal in one half triangular region of matrix.diagonal_offset = 0is the main diagonal,diagonal_offset > 0means ignore this many bins from the diagonal. - corrType (str) – Correlation type. For Pearson and Spearman rank-order correlation, use
pearsonandspearman, respectively. - blockSize (str) – To calculate block-wise correlations by sliding block of given size along diagonals. It should be in resolution.
For example,
1mb,500kb,5mb,2.5mbetc. IfNone, correlation of whole map is calculated. Sliding step of block depends onslideStepSize. - slideStepSize (int) – Step-size in bins by which blocks will be shifted for block-wise correlation. If slideStepSize is large then blocks might not be overlapped.
- workDir (str) – Name of working directory, where temporary files will be kept.If
workDir = None, file will be generated in OS based temporary directory. - outFile (str) – Name of output file. Only written for block-wise correlation.
Returns: - corr (float or list) – Correlation coefficient
- pvalue/centers (float or list) – If
blockSize=None2-tailed p-value is returned. For block-wise correlation, list of block-center is returned.
See also
- scipy.stats.stats.pearsonr for Pearson correlation.
- scipy.stats.stats.spearmanr for Spearman rank-order correlation.
- ccMapObjOne (
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getAvgContactByDistance(ccmaps, stats='median')¶ To calcualte average contact as a function of distance
Parameters: hicmaps ( gcMapExplorer.lib.ccmap.CCMAPor list[gcMapExplorer.lib.ccmap.CCMAP]) –Returns: avg_contacts – A one-dimensional numpy array containing average contacts, where index is distance between two locations for given resolution/binsize. For example, if ccmap.binsize=100000andavg_contacts[4]=1234.56, then at distance of 400000 b, average contact is1234.56.Return type: numpy.array