X is a design matrix and W is a latent factor matrix representing non-biological variation. W is unobserved with dimension kxJ, where k is an un-known parameter and J is the number of features in the data. With the additional unknown parameters α and β the regression model becomes underdetermined. But the design matrix X is known since we know the sample identities.