Median of ratios normalization As used by Deseq2, see: https://github.com/hbctraining/DGE_workshop/blob/master/lessons/02_DGE_count_normalization.md . Rows are genes, columns are samples

data : Matrix<float>

data matrix with columns as features (samples,time points) and rows as measured entities (genes,proteins).

Returns: MorResult

Normalized data matrix with correction factors and normalization function.

Example

 
   // raw data with proteins as rows and samples as columns
   let myData = Matrix.init 500 5 (fun _ _ -> rnd.NextDouble())
   let normedData = Normalization.medianOfRatios myData

Median of ratios normalization As used by Deseq2, see: https://github.com/hbctraining/DGE_workshop/blob/master/lessons/02_DGE_count_normalization.md . Rows are genes, columns are samples

f : float -> float

The transformation function is applied on all values of the matrix before calculating the normalization factors.

data : Matrix<float>

data matrix with columns as features (samples,time points) and rows as measured entities (genes,proteins).

Returns: MorResult

Normalized data matrix with correction factors and normalization function.

Example

 
   // raw data with proteins as rows and samples as columns
   let myData = Matrix.init 500 5 (fun _ _ -> rnd.NextDouble())
   let normedData = Normalization.medianOfRatiosBy (fun x -> ln (x+1)) myData

Median of ratios normalization As used by Deseq2, see: https://github.com/hbctraining/DGE_workshop/blob/master/lessons/02_DGE_count_normalization.md . Columns are genes, rows are samples

data : Matrix<float>

data matrix with columns as measured entities and rows as features (samples,time points) (genes,proteins).

Returns: MorResult

Normalized data matrix with correction factors and normalization function.

Example

 
   // raw data with proteins as columns and samples as rows
   let myData = Matrix.init 5 500 (fun _ _ -> rnd.NextDouble())
   let normedData = Normalization.medianOfRatiosWide myData

Median of ratios normalization As used by Deseq2, see: https://github.com/hbctraining/DGE_workshop/blob/master/lessons/02_DGE_count_normalization.md . Columns are genes, rows are samples

f : float -> float

The transformation function is applied on all values of the matrix before calculating the normalization factors.

data : Matrix<float>

data matrix with columns as measured entities and rows as features (samples,time points) (genes,proteins).

Returns: MorResult

Normalized data matrix with correction factors and normalization function.

Example

 
   // raw data with proteins as columns and samples as rows
   let myData = Matrix.init 5 500 (fun _ _ -> rnd.NextDouble())
   let normedData = Normalization.medianOfRatiosWideBy (fun x -> ln (x+1)) myData

Quantile normalization with equal number of elements (rows) for each sample (column). Column mean and column standard deviation are qual after normalization. Rows are genes, columns are samples.

data : Matrix<float>

data matrix with columns as measured entities and rows as features (samples,time points) (genes,proteins).

Returns: Matrix<float>

Normalized data matrix.

Example

 
   // raw data with proteins as rows and samples as columns
   let myData = Matrix.init 500 5 (fun _ _ -> rnd.NextDouble())
   let normedData = Normalization.quantile myData

z score normalization/transformation using the sample standard deviation. Rarely used since variance is not equal to 1.

Bortz J., Schuster C., Statistik für Human- und Sozialwissenschaftler, 7 (2010), p. 35

yVal : Vector<float>

Returns: Vector<float>

transformed yData in unchanged order

Example

 
   // transform data, such that data has zero mean and sample standard deviation of 1
   Normalization.zScoreTransform (vector [|1.1;5.3;-9.0;13.2;17.3;-2.3|])

z score normalization/transformation using the population standard deviation.

Bortz J., Schuster C., Statistik für Human- und Sozialwissenschaftler, 7 (2010), p. 35

yVal : Vector<float>

Returns: Vector<float>

transformed yData in unchanged order

Example

 
   // transform data, such that data has zero mean and population standard deviation of  
   Normalization.zScoreTransformPopulation (vector [|1.1;5.3;-9.0;13.2;17.3;-2.3|])