Information and statistics¶
Get information¶
stats.print_info(obj)
Prints information about the number of samples, number of reads, minimum and maximum number of reads in a samples, meta data, taxonomy, etc.
stats.taxa(obj, savename='None')
Returns a pandas dataframe with information about the number of taxa at different taxonomic levels in the data.
obj is an object.
if savename is specified, a csv file with the information is saved.
Mantel test¶
stats.mantel(dis1, dis2, method='spearman', getOnlyStat=False, permutations=99)
Carries out a mantel tests and returns a list containing the test statistic and the p value.
dis1 and dis2 are two dissimilarity matrices.
method is the test statistic used. ‘spearman’, ‘pearson’, or ‘absDist’ can be chosen. The methods converts each dissimilarity matrix to an array of numbers and investigates the correlation between the two arrays.
- ‘spearman’ is a rank-based correlation coefficient.
- ‘pearson’ is the product-moment correlation coefficient conventionally used in the Mantel test.
- ‘absDist’ is the mean absolute distance between the numbers in the two arrays.
If getOnlyStat =True, only the test statistic will be returned, no permutations and consequently no p-value will be calculated.
permutations is the number of randomizations carried out.
Permanova¶
stats.permanova(dis, meta, var, permutations=99)
Carries out a permanova tests and returns a list containing the test statistic and the p value.
dis is a dissimilarity matrix.
meta is the meta data, e.g. obj[‘meta’].
var is the column in the meta data that holds the categories of samples being compared.
permutations is the number of randomizations carried out.
Distance between sequences¶
stats.sequence_comparison(obj, inputType='seq', savename='DistMat')
Returns a pandas dataframe with pairwise distances between OTUs/ASVs in the data set. The data is also saved as a csv file at the location specified by savename.
obj is the qdiv object.
inputType can be either ‘seq’ or ‘tree’. If it is ‘seq’, the distance is calculated as the Levenshtein distance dividied by the length of the longest distance in the pair. If it is ‘tree’, the distances are calculated as branch distances in the phylogenetic tree.
savename specifies path and name of output file.