For some analyses you might be interested in transforming the counts into RPKMs which you can do with this function.
getRPKM(rse, length_var = "bp_length", mapped_var = NULL)A RangedSummarizedExperiment-class object as downloaded with download_study.
A length 1 character vector with the column name from
rowData(rse) that has the coding length. For gene level objects
from recount this is bp_length. If NULL, then it will use
width(rowRanges(rse)) which should be used for exon RSEs.
A length 1 character vector with the column name from
colData(rse) that has the number of reads mapped. For recount RSE
object this would be mapped_read_count. If NULL (default)
then it will use the column sums of the counts matrix. The results are
different because not all mapped reads are mapped to exonic segments of the
genome.
A matrix with the RPKM values.
For gene RSE objects, you will want to specify the length_var
because otherwise you will be adjusting for the total gene length instead
of the total exonic sequence length of the gene.
## get RPKM matrix
rpkm <- getRPKM(rse_gene_SRP009615)
## You can also get an RPKM matrix after running scale_counts()
## with similar RPKM values
rpkm2 <- getRPKM(scale_counts(rse_gene_SRP009615))
rpkm3 <- getRPKM(scale_counts(rse_gene_SRP009615, by = "mapped_reads"))
summary(rpkm - rpkm2)
#> SRR387777 SRR387778 SRR387779
#> Min. :-0.538140 Min. :-0.496618 Min. :-0.2782572
#> 1st Qu.:-0.001367 1st Qu.:-0.001441 1st Qu.:-0.0007156
#> Median : 0.000000 Median : 0.000000 Median : 0.0000000
#> Mean : 0.001328 Mean : 0.001216 Mean : 0.0005080
#> 3rd Qu.: 0.001639 3rd Qu.: 0.002102 3rd Qu.: 0.0014124
#> Max. : 0.459320 Max. : 0.412033 Max. : 0.5638757
#> SRR387780 SRR389077 SRR389078
#> Min. :-0.275124 Min. :-0.3686954 Min. :-1.762821
#> 1st Qu.:-0.001091 1st Qu.:-0.0017073 1st Qu.:-0.001882
#> Median : 0.000000 Median : 0.0000000 Median : 0.000000
#> Mean : 0.000969 Mean :-0.0009294 Mean : 0.001999
#> 3rd Qu.: 0.001363 3rd Qu.: 0.0014684 3rd Qu.: 0.002319
#> Max. : 0.352192 Max. : 0.8665052 Max. : 0.640973
#> SRR389079 SRR389080 SRR389081
#> Min. :-0.3599736 Min. :-0.3056064 Min. :-0.4041139
#> 1st Qu.:-0.0021947 1st Qu.:-0.0007341 1st Qu.:-0.0014252
#> Median : 0.0000000 Median : 0.0000000 Median : 0.0000000
#> Mean :-0.0006854 Mean : 0.0008586 Mean :-0.0006136
#> 3rd Qu.: 0.0015759 3rd Qu.: 0.0010928 3rd Qu.: 0.0007495
#> Max. : 0.3829134 Max. : 0.2733806 Max. : 0.3281689
#> SRR389082 SRR389083 SRR389084
#> Min. :-0.2330620 Min. :-0.3047474 Min. :-0.3486800
#> 1st Qu.:-0.0004445 1st Qu.:-0.0010143 1st Qu.:-0.0009503
#> Median : 0.0000000 Median : 0.0000000 Median : 0.0000000
#> Mean : 0.0005996 Mean :-0.0006126 Mean :-0.0003374
#> 3rd Qu.: 0.0007402 3rd Qu.: 0.0006283 3rd Qu.: 0.0004121
#> Max. : 0.2488342 Max. : 0.4275825 Max. : 0.3975724
summary(rpkm - rpkm3)
#> SRR387777 SRR387778 SRR387779
#> Min. :-0.2136981 Min. :-0.1968742 Min. :-2.885e-01
#> 1st Qu.:-0.0006772 1st Qu.:-0.0005507 1st Qu.:-4.843e-04
#> Median : 0.0000000 Median : 0.0000000 Median : 0.000e+00
#> Mean :-0.0002927 Mean : 0.0004231 Mean :-9.456e-05
#> 3rd Qu.: 0.0004006 3rd Qu.: 0.0007176 3rd Qu.: 1.540e-04
#> Max. : 0.1130460 Max. : 0.1770789 Max. : 1.006e-01
#> SRR387780 SRR389077 SRR389078
#> Min. :-0.1577897 Min. :-0.5299857 Min. :-0.1891372
#> 1st Qu.:-0.0004845 1st Qu.:-0.0005405 1st Qu.:-0.0009724
#> Median : 0.0000000 Median : 0.0000000 Median : 0.0000000
#> Mean :-0.0001782 Mean : 0.0007128 Mean :-0.0002439
#> 3rd Qu.: 0.0004263 3rd Qu.: 0.0006473 3rd Qu.: 0.0004048
#> Max. : 0.1376846 Max. : 0.2552746 Max. : 0.3569628
#> SRR389079 SRR389080 SRR389081
#> Min. :-0.1176256 Min. :-0.1430089 Min. :-0.1853069
#> 1st Qu.:-0.0006174 1st Qu.:-0.0002933 1st Qu.:-0.0002045
#> Median : 0.0000000 Median : 0.0000000 Median : 0.0000000
#> Mean : 0.0002104 Mean : 0.0003596 Mean : 0.0001303
#> 3rd Qu.: 0.0007492 3rd Qu.: 0.0003547 3rd Qu.: 0.0004992
#> Max. : 0.1201767 Max. : 0.1114920 Max. : 0.1054893
#> SRR389082 SRR389083 SRR389084
#> Min. :-0.1564435 Min. :-1.436e-01 Min. :-1.010e-01
#> 1st Qu.:-0.0002348 1st Qu.:-4.315e-04 1st Qu.:-3.699e-05
#> Median : 0.0000000 Median : 0.000e+00 Median : 0.000e+00
#> Mean : 0.0003452 Mean :-1.422e-04 Mean : 1.435e-04
#> 3rd Qu.: 0.0002462 3rd Qu.: 9.928e-05 3rd Qu.: 3.646e-04
#> Max. : 0.1086730 Max. : 9.926e-02 Max. : 9.869e-02
summary(rpkm2 - rpkm3)
#> SRR387777 SRR387778 SRR387779
#> Min. :-0.507532 Min. :-0.445699 Min. :-0.8523319
#> 1st Qu.:-0.001622 1st Qu.:-0.002041 1st Qu.:-0.0014352
#> Median : 0.000000 Median : 0.000000 Median : 0.0000000
#> Mean :-0.001621 Mean :-0.000793 Mean :-0.0006026
#> 3rd Qu.: 0.001416 3rd Qu.: 0.001372 3rd Qu.: 0.0007158
#> Max. : 0.422133 Max. : 0.673697 Max. : 0.3589322
#> SRR387780 SRR389077 SRR389078
#> Min. :-0.461343 Min. :-1.388253 Min. :-0.491700
#> 1st Qu.:-0.001245 1st Qu.:-0.001551 1st Qu.:-0.002401
#> Median : 0.000000 Median : 0.000000 Median : 0.000000
#> Mean :-0.001147 Mean : 0.001642 Mean :-0.002243
#> 3rd Qu.: 0.001177 3rd Qu.: 0.001683 3rd Qu.: 0.001885
#> Max. : 0.305930 Max. : 0.505786 Max. : 2.119784
#> SRR389079 SRR389080 SRR389081
#> Min. :-0.3710228 Min. :-0.3038938 Min. :-0.4838542
#> 1st Qu.:-0.0016096 1st Qu.:-0.0010920 1st Qu.:-0.0007814
#> Median : 0.0000000 Median : 0.0000000 Median : 0.0000000
#> Mean : 0.0008958 Mean :-0.0004991 Mean : 0.0007439
#> 3rd Qu.: 0.0022193 3rd Qu.: 0.0006149 3rd Qu.: 0.0014597
#> Max. : 0.4049808 Max. : 0.3143154 Max. : 0.4810074
#> SRR389082 SRR389083 SRR389084
#> Min. :-0.3190688 Min. :-0.4729762 Min. :-0.3743508
#> 1st Qu.:-0.0007932 1st Qu.:-0.0006477 1st Qu.:-0.0004526
#> Median : 0.0000000 Median : 0.0000000 Median : 0.0000000
#> Mean :-0.0002543 Mean : 0.0004705 Mean : 0.0004809
#> 3rd Qu.: 0.0005059 3rd Qu.: 0.0010338 3rd Qu.: 0.0009586
#> Max. : 0.3414912 Max. : 0.2808215 Max. : 0.3405986