Hi a-h-b,
I have a big data set with similar sequencing depth per sample (30,000-40,000). However, around 10 % of the samples have a sequencing depth of more than 100,000. Since the number of raw reads affects the number of OTUs, I want to reduce such outliers by downsampling. Therefore, I used the downsampling function with min = false to avoid the removal of samples below this threshold.
downsampling:
do: true
number: 40000
min: false
seed: 123
use_total: false
total: 100000000
Unfortunately, dadasnake still removed all samples with less than 40,000 reads. Is the setting wrong or have I made another mistake or perhaps a bug?
Thank you for your help, juismo
Hi a-h-b,
I have a big data set with similar sequencing depth per sample (30,000-40,000). However, around 10 % of the samples have a sequencing depth of more than 100,000. Since the number of raw reads affects the number of OTUs, I want to reduce such outliers by downsampling. Therefore, I used the downsampling function with min = false to avoid the removal of samples below this threshold.
downsampling:
do: true
number: 40000
min: false
seed: 123
use_total: false
total: 100000000
Unfortunately, dadasnake still removed all samples with less than 40,000 reads. Is the setting wrong or have I made another mistake or perhaps a bug?
Thank you for your help, juismo