Hi guys, first off, I'm new to this forum... hi everybody!

Lately, I've been working with data for comparing peptide activity on modified peptides. We have a parent peptide (full activity), and a control peptide (minimal activity).

Between them are a range of different activities. We have means, n values and SEMs for all the different values.

The data looks sort of like this (the numbers are arbitrarily assigned):

Parent: value-100, SEM-10, n=30

Control: value-20, SEM-5, n=25

A: value-40, SEM-6, n=27

B: value-70...

C: ...

D: ...

etc.

The data is assumed to be Gaussian distribution.

My question is this:Is there a statistical test that can help me determine whether the experimental peptides (A, B, C... etc.) are EITHER significantly different Parent OR Control?

The reason I ask this question is because we've tried both unpaired T-tests and ANOVA analysis with a Dunnett's post test (along with a host of other 1-tailed ANOVA tests + post test) . However, in every situation, we've found that certain peptides (peptide D for example) is NOT significantly different from the control OR parent peptide.

We've also found that certain peptides (peptide E for example) are significantly different from the control AND the parent peptide. How is this possible and can it be resolved?

We would ultimately like to be able to say that "Peptide X is significantly different from (Control OR experimental)", but with the statistical data we currently have, this is not possible.

Thank you guys in advance for any help and I apologize for the long post!

-Elton