By default, the PCA and t-SNE plots are produced using the features with the most variable expression across all cells, though this can be changed with function arguments.
The ability to change the function parameters is implied by the "By default" and in the rest of the paragraph where we talk about other types of gene sets that can be used. There's no need to mention it explicitly.
By default, the PCA and t-SNE plots are produced using the features with the most variable expression across all cells.
The subsetting and filtering methods for SCESet objects make it easy to construct reduced-dimension plots for particular gene sets, in order to investigate certain effects in the data, such as those due to the cell cycle (Figure 3d–f).
Pretty sure you don't need a comma here:
The subsetting and filtering methods for SCESet objects make it easy to construct reduced-dimension plots for particular gene sets, in order to investigate certain effects in the data such as those due to the cell cycle (Figure 3d–f).
The ability to change the function parameters is implied by the "By default" and in the rest of the paragraph where we talk about other types of gene sets that can be used. There's no need to mention it explicitly.
Pretty sure you don't need a comma here: