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Step 1: Get three parameters from the user :
Min expression level (min.count) : Double
Min total expression count (min.total.count) : Double (Optional parameter)
Number of samples having minimum expression (n) : Integer
Step 2: For each gene, check if atleast n number of included samples have expression level > min.count If yes, then the gene should be retained, else, it should be filtered out.
Step 3: Default value of n should be Ceil( Total number of included samples * 0.1)
Step 4: If the user also provides the optional parameter min.total.count, then among the genes obtained after the filtering in the above steps, check whether the total expression count across all the included samples is greater than min.total.count. If yes, then retain the gene, else filter it out.
Step 5: If the user does not provide min.total.count, then do not perform the additional filtering in step 4.
Success Criteria: The rows in the feature metadata table must be properly filtered based on the expression levels provided. The filtering must work even when the user includes only a subset of the samples.
The text was updated successfully, but these errors were encountered:
We want to add an entirely new feature where users can filter rows in the table based on expression data.
The functionality should be similar to this R method (Please read the “Details” section) https://rdrr.io/bioc/edgeR/man/filterByExpr.html
Gist of the functionality:
Step 1: Get three parameters from the user :
Min expression level (min.count) : Double
Min total expression count (min.total.count) : Double (Optional parameter)
Number of samples having minimum expression (n) : Integer
Step 2: For each gene, check if atleast n number of included samples have expression level > min.count If yes, then the gene should be retained, else, it should be filtered out.
Step 3: Default value of n should be Ceil( Total number of included samples * 0.1)
Step 4: If the user also provides the optional parameter min.total.count, then among the genes obtained after the filtering in the above steps, check whether the total expression count across all the included samples is greater than min.total.count. If yes, then retain the gene, else filter it out.
Step 5: If the user does not provide min.total.count, then do not perform the additional filtering in step 4.
Success Criteria: The rows in the feature metadata table must be properly filtered based on the expression levels provided. The filtering must work even when the user includes only a subset of the samples.
The text was updated successfully, but these errors were encountered: