rnalysis.filtering

Description

This module can filter, normalize, intersect and visualize tabular data such as read counts and differential expression data. Any tabular data saved in a csv format can be imported. Use this module to perform various filtering operations on your data, normalize your data, perform set operations (union, intersection, etc), run basic exploratory analyses and plots (such as PCA, clustergram, violin plots, scatter, etc), save the filtered data to your computer, and more. When you save filtered/modified data, its new file name will include by default all of the operations performed on it, in the order they were performed, to allow easy traceback of your analyses.

Classes

CountFilter(fname[, drop_columns, is_normalized])	A class that receives a count matrix and can filter it according to various characteristics.
DESeqFilter(fname[, drop_columns, ...])	A class that receives a DESeq output file and can filter it according to various characteristics.
Filter(fname[, drop_columns])	An all-purpose Filter object.
FoldChangeFilter(fname, numerator_name, ...)	A class that contains a single column, representing the gene-specific fold change between two conditions.
Pipeline(filter_type, ...)	A collection of functions to be applied sequentially to Filter objects.