Get smoothers estimated by tradeSeq along a grid. This function does not return fitted values but rather the predicted mean smoother, for a user-defined grid of points.

predictSmooth(models, ...)

# S4 method for SingleCellExperiment
predictSmooth(models, gene, nPoints = 100, tidy = TRUE)

# S4 method for list
predictSmooth(models, gene, nPoints = 100)



Either the SingleCellExperiment object obtained after running fitGAM, or the specific GAM model for the corresponding gene, if working with the list output of tradeSeq.


parameters including:


Either a vector of gene names or an integer vector, corresponding to the row(s) of the gene(s).


The number of points used to create the grid along the smoother for each lineage. Defaults to 100.


Logical: return tidy output. If TRUE, returns a data.frame specifying lineage, gene, pseudotime and value of estimated smoother. If FALSE, returns matrix of predicted smoother values, where each row is a gene and each column is a point on the uniform grid along the lineage. For example, if the trajectory consists of 2 lineages and nPoints=100, then the returned matrix will have 2*100 columns, where the first 100 correspond to the first lineage and columns 101-200 to the second lineage.


A matrix with estimated averages.

A vector of fitted values.


Using the gene expression model of tradeSeq available at the output of predictSmooth returns the \(\eta_{gi}\) value for equally space values of pseudotimes, and a constant value for \(U_i\) and \(N_i\) (arbitraly, we select the values of \(i=1\)).


data(gamList, package = "tradeSeq") predictSmooth(models = gamList, gene = 1)
#> lineage1_1 lineage1_2 lineage1_3 lineage1_4 lineage1_5 lineage1_6 #> 1 6.787343e-18 6.848751e-18 6.910715e-18 6.97324e-18 7.03633e-18 7.099992e-18 #> lineage1_7 lineage1_8 lineage1_9 lineage1_10 lineage1_11 lineage1_12 #> 1 7.164229e-18 7.229047e-18 7.294452e-18 7.360448e-18 7.427042e-18 7.494238e-18 #> lineage1_13 lineage1_14 lineage1_15 lineage1_16 lineage1_17 lineage1_18 #> 1 7.562042e-18 7.630459e-18 7.699496e-18 7.769157e-18 7.839448e-18 7.910376e-18 #> lineage1_19 lineage1_20 lineage1_21 lineage1_22 lineage1_23 lineage1_24 #> 1 7.981945e-18 8.054161e-18 8.127031e-18 8.20056e-18 8.274755e-18 8.349621e-18 #> lineage1_25 lineage1_26 lineage1_27 lineage1_28 lineage1_29 lineage1_30 #> 1 8.425164e-18 8.50139e-18 8.578307e-18 8.655919e-18 8.734233e-18 8.813256e-18 #> lineage1_31 lineage1_32 lineage1_33 lineage1_34 lineage1_35 lineage1_36 #> 1 8.892994e-18 8.973453e-18 9.05464e-18 9.136562e-18 9.219225e-18 9.302636e-18 #> lineage1_37 lineage1_38 lineage1_39 lineage1_40 lineage1_41 lineage1_42 #> 1 9.386801e-18 9.471728e-18 9.557424e-18 9.643894e-18 9.731147e-18 9.81919e-18 #> lineage1_43 lineage1_44 lineage1_45 lineage1_46 lineage1_47 lineage1_48 #> 1 9.908029e-18 9.997672e-18 1.008813e-17 1.01794e-17 1.02715e-17 1.036443e-17 #> lineage1_49 lineage1_50 lineage1_51 lineage1_52 lineage1_53 lineage1_54 #> 1 1.04582e-17 1.055282e-17 1.06483e-17 1.074464e-17 1.084185e-17 1.093994e-17 #> lineage1_55 lineage1_56 lineage1_57 lineage1_58 lineage1_59 lineage1_60 #> 1 1.103892e-17 1.113879e-17 1.123957e-17 1.134126e-17 1.144387e-17 1.154741e-17 #> lineage1_61 lineage1_62 lineage1_63 lineage1_64 lineage1_65 lineage1_66 #> 1 1.165188e-17 1.175731e-17 1.186368e-17 1.197102e-17 1.207932e-17 1.218861e-17 #> lineage1_67 lineage1_68 lineage1_69 lineage1_70 lineage1_71 lineage1_72 #> 1 1.229889e-17 1.241016e-17 1.252244e-17 1.263574e-17 1.275006e-17 1.286542e-17 #> lineage1_73 lineage1_74 lineage1_75 lineage1_76 lineage1_77 lineage1_78 #> 1 1.298182e-17 1.309927e-17 1.321778e-17 1.333737e-17 1.345804e-17 1.35798e-17 #> lineage1_79 lineage1_80 lineage1_81 lineage1_82 lineage1_83 lineage1_84 #> 1 1.370267e-17 1.382664e-17 1.395174e-17 1.407797e-17 1.420534e-17 1.433386e-17 #> lineage1_85 lineage1_86 lineage1_87 lineage1_88 lineage1_89 lineage1_90 #> 1 1.446354e-17 1.45944e-17 1.472645e-17 1.485968e-17 1.499413e-17 1.512979e-17 #> lineage1_91 lineage1_92 lineage1_93 lineage1_94 lineage1_95 lineage1_96 #> 1 1.526667e-17 1.54048e-17 1.554417e-17 1.568481e-17 1.582672e-17 1.596991e-17 #> lineage1_97 lineage1_98 lineage1_99 lineage1_100 lineage2_1 lineage2_2 #> 1 1.61144e-17 1.626019e-17 1.64073e-17 1.655575e-17 1.19713e-17 1.195417e-17 #> lineage2_3 lineage2_4 lineage2_5 lineage2_6 lineage2_7 lineage2_8 #> 1 1.193706e-17 1.191998e-17 1.190292e-17 1.188589e-17 1.186888e-17 1.18519e-17 #> lineage2_9 lineage2_10 lineage2_11 lineage2_12 lineage2_13 lineage2_14 #> 1 1.183494e-17 1.1818e-17 1.180109e-17 1.17842e-17 1.176734e-17 1.17505e-17 #> lineage2_15 lineage2_16 lineage2_17 lineage2_18 lineage2_19 lineage2_20 #> 1 1.173369e-17 1.171689e-17 1.170013e-17 1.168339e-17 1.166667e-17 1.164997e-17 #> lineage2_21 lineage2_22 lineage2_23 lineage2_24 lineage2_25 lineage2_26 #> 1 1.16333e-17 1.161665e-17 1.160003e-17 1.158343e-17 1.156685e-17 1.15503e-17 #> lineage2_27 lineage2_28 lineage2_29 lineage2_30 lineage2_31 lineage2_32 #> 1 1.153377e-17 1.151727e-17 1.150079e-17 1.148433e-17 1.14679e-17 1.145149e-17 #> lineage2_33 lineage2_34 lineage2_35 lineage2_36 lineage2_37 lineage2_38 #> 1 1.14351e-17 1.141873e-17 1.140239e-17 1.138608e-17 1.136978e-17 1.135351e-17 #> lineage2_39 lineage2_40 lineage2_41 lineage2_42 lineage2_43 lineage2_44 #> 1 1.133727e-17 1.132104e-17 1.130484e-17 1.128867e-17 1.127251e-17 1.125638e-17 #> lineage2_45 lineage2_46 lineage2_47 lineage2_48 lineage2_49 lineage2_50 #> 1 1.124027e-17 1.122419e-17 1.120813e-17 1.119209e-17 1.117607e-17 1.116008e-17 #> lineage2_51 lineage2_52 lineage2_53 lineage2_54 lineage2_55 lineage2_56 #> 1 1.114411e-17 1.112816e-17 1.111224e-17 1.109634e-17 1.108046e-17 1.10646e-17 #> lineage2_57 lineage2_58 lineage2_59 lineage2_60 lineage2_61 lineage2_62 #> 1 1.104877e-17 1.103296e-17 1.101717e-17 1.10014e-17 1.098566e-17 1.096994e-17 #> lineage2_63 lineage2_64 lineage2_65 lineage2_66 lineage2_67 lineage2_68 #> 1 1.095424e-17 1.093857e-17 1.092291e-17 1.090728e-17 1.089167e-17 1.087609e-17 #> lineage2_69 lineage2_70 lineage2_71 lineage2_72 lineage2_73 lineage2_74 #> 1 1.086052e-17 1.084498e-17 1.082946e-17 1.081397e-17 1.079849e-17 1.078304e-17 #> lineage2_75 lineage2_76 lineage2_77 lineage2_78 lineage2_79 lineage2_80 #> 1 1.076761e-17 1.07522e-17 1.073681e-17 1.072145e-17 1.070611e-17 1.069079e-17 #> lineage2_81 lineage2_82 lineage2_83 lineage2_84 lineage2_85 lineage2_86 #> 1 1.067549e-17 1.066021e-17 1.064496e-17 1.062972e-17 1.061451e-17 1.059932e-17 #> lineage2_87 lineage2_88 lineage2_89 lineage2_90 lineage2_91 lineage2_92 #> 1 1.058416e-17 1.056901e-17 1.055389e-17 1.053878e-17 1.05237e-17 1.050864e-17 #> lineage2_93 lineage2_94 lineage2_95 lineage2_96 lineage2_97 lineage2_98 #> 1 1.049361e-17 1.047859e-17 1.046359e-17 1.044862e-17 1.043367e-17 1.041874e-17 #> lineage2_99 lineage2_100 #> 1 1.040383e-17 1.038894e-17