text: ### our filtered subsets have different genes kept (after the low expression cut) so we need to select only genes that are present in both filtered subsets
  import pandas as pd
  subset_a=pd.read_csv('rootsub_filtered.csv', header=0, index_col=0)
  subset_b=pd.read_csv('leafsub_filtered.csv', header=0, index_col=0)
  
  print("subset a shape is", subset_a.shape) #what do these look like to start
  print("subset b shape is", subset_b.shape)
  
  samegenes = subset_a.index.intersection(subset_b.index) # make variable of conserved genes between the two filtered subsets
  subset_a = subset_a[subset_a.index.isin(samegenes)] #reduce to only those genes
  subset_b = subset_b[subset_b.index.isin(samegenes)]
  print(len(samegenes), "genes conserved,\nsubset a new shape is",subset_a.shape, "subset b new shape is", subset_b.shape) # make sure thins look okay
  
  subset_a.to_csv('root_consensus.csv') # make the csv
  subset_b.to_csv('leaf_consensus.csv')
  