A
Arto Vesterbacka
Hi,
I'm trying to normalize a large data set to remove errors caused b
equipment. I have 101 columns (samples) that are in time order b
column. These columns include multiple quality control samples (1 i
every 10 or so) that should have all close to equal values. Thes
however go down linearly and therefore all the data is transformed dow
(seen in replicate samples place randomly across the running order). Th
first and last sample are QCs. Is there a way to scale up all the value
so that the QCs would be ~equal and my data would be transformed
I'm trying to normalize a large data set to remove errors caused b
equipment. I have 101 columns (samples) that are in time order b
column. These columns include multiple quality control samples (1 i
every 10 or so) that should have all close to equal values. Thes
however go down linearly and therefore all the data is transformed dow
(seen in replicate samples place randomly across the running order). Th
first and last sample are QCs. Is there a way to scale up all the value
so that the QCs would be ~equal and my data would be transformed