Expression levels, review

[mdelrio1]

@sr320
Hi Steven
I think we may have an issue with the expression levels. if you look at the file
paper-pano-go/data-results/Male-v-Female-Expression.csv
in line 88, you will see a "#NAME?" datum in column "Experiment - Fold Change (original values)"

comp144391_c0_seq2,6024,-6024,#NAME?,462,6024,0,0

or in line
comp144300_c0_seq10,2,2,âˆ_,0,0,0,2

you'll see a "âˆ_".
I replaced both with zero in the whole table!!!
But, in the first case males have expression (females=0), while in the second case is there reverse (females have expression, males=0).
When I obtained the data for the big table I used this column, "Experiment - Fold Change (original values)", to calculate whether the expression value was male, female
See notebook paper-pano-go/jupyter-nbs/10Panopea_databases.ipynb
In [31]: line 7 "if row["fold_change"]>100" and so on.

This means that we did not consider the contigs where there was a value of zero in the "Female-Total" or "Male-Total"
I'm going to run again this withe the original data, but considering:
female: ['female_unique']>0, ['male_unique']=0
male: ['female_unique']=0, ['male_unique']>0
female>male ['female_unique']/ ['male_unique']>100
male>female ['female_unique']/ ['male_unique']<.01

[mdelrio1]

@sr320
Hi I have uploaded a version 9 of the big table. I have calculated the expression levels and check if they are
female
female>male
male
male>female
considering
a) female, male=0, female >100 (counts)
b) female>male, expression male/ expression female >100
c) male, female=0, male > 100 (counts)
d) male>female, expression male/ expression female >0.01

is this clear? I hope so.