abagen.keep_stable_genes

abagen.keep_stable_genes(expression, threshold=0.9, percentile=True, rank=True, return_stability=False)[source]

Removes genes in expression with differential stability < threshold

Calculates the similarity of gene expression across brain regions for every pair of donors in expression. Similarity is averaged across donor pairs and genes whose mean similarity falls below threshold are removed.

Parameters:

  • expression (list of (R, G) pandas.DataFrame) – Where each entry is the microarray expression of R regions across G genes for a given donor

  • threshold ([0, 1] float, optional) – Minimum required average similarity (e.g, correlation) across donors for a gene to be retained. Default: 0.1

  • percentile (bool, optional) – Whether to treat threshold as a percentile instead of an absolute cutoff. For example, threshold=0.9 and percentile=True would retain only those genes with a differential stability in the top 10% of all genes, whereas percentile=False would retain only those genes with differential stability > 0.9. Default: True

  • rank (bool, optional) – Whether to calculate similarity as Spearman correlation instead of Pearson correlation. Default: True

  • return_stability (bool, optional) – Whether to return stability estimates for each gene in addition to expression data. Default: False

Returns:

  • expression (list of (R, Gr) pandas.DataFrame) – Microarray expression for R regions across Gr genes, where Gr is the number of retained genes

  • stability ((G,) numpy.ndarray) – Stability (average correlation) of each gene across pairs of donors. Only returned if return_stability=True