Step 4 - TEI calculation

The phylogenetically based transcriptome evolutionary index (TEI) is similar to Domazet-Loso & Tautz, 2010.

The TEI measure represents the weighted arithmetic mean (expression levels as weights for the phylostratum value) over all evolutionary age categories denoted as phylostra.

\[TEI_s = \sum (e_{is} * ps_i) / \sum e_{is}\]

where \(TEI_s\) denotes the TEI value in developmental stage \(s, e_{is}\) denotes the gene expression level of gene \(i\) in stage \(s\), and \(ps_i\) denotes the corresponding phylostratum of gene \(i, i = 1,...,N\) and \(N = total\ number\ of\ genes\).

Note

Please have a look at Liu & Robinson-Rechavi, 2018 to get more insides how expression transformation can influence TEI calculation. By default, the expression values are pre-processed. This includes normalizing the counts per cell (see option normalize_total) to a total count of 1e6 (which corresponds to CPM; see option target_sum) and log-transformed (see option log1p).

How to add a transcriptome evolutionary index (short: TEI) to scRNA data

Please download the notebooks from here or please click below to view the content.

• oggmap: Step 4 - TEI calculation
  • Notebook file
  • Import libraries
  • Import oggmap python package submodules
  • Step 0, Step 1, Step 2 and Step 3
    • Step 0 - run OrthoFinder
    • Step 1 - get taxonomic information
    • Step 2 - gene age class assignment
    • Step 3 - map gene/transcript IDs
    • Import now, the scRNA dataset of the query species
  • Step 4 - Get TEI values and add them to scRNA dataset
    • add TEI to adata object
    • Boxplot gene age class per embryo stage
    • calculate bootstrap on subet of the data