Filtering information from one table to be combined with information of another table using R

Question

Someone can help me to solve this trick? I have two tables as I will show you below (data1 and data2). I would like to output (data3) combining both. The idea is to select only negative values from each "mir" (mir.1, mir2, ..., mir25) from data1, combining the information of the respective "mir" from data2 to generate the data3.

Exemple:

data1 <-"P_G,mir-1,mir-2,mir-3,mir-4,mir-5,mir-6,mir-7,mir-8,mir-9,mir-10,mir-11,mir-12,mir-13,mir-14,mir-15,mir-16,mir-17,mir-18,mir-19,mir-20,mir-21,mir-22,mir-23,mir-24,mir-25
P111179_ENSBTAG00000005989,NA,0.27,NA,NA,NA,NA,NA,-0.19,0.3580,NA,0.5234,-0.58,-0.24,-0.50,NA,NA,-0.11,-0.37,NA,NA,0.41,0.20,NA,-0.32,NA
P137378_ENSBTAG00000038920,-0.09231,-0.30,NA,-0.02,0.2158,-0.16,-0.08,-0.41,-0.21,-0.21,-0.49,0.6939,-0.08,0.6030,0.6030,-0.15,0.5506,0.0810,-0.38,NA,0.36,-0.44,0.26,0.05,-0.10
P136511_8_ENSBTAG00000043999,0.40317,0.38,NA,0.6185,-0.15,0.6674,-0.47,0.0065,0.2911,0.2911,0.3999,-0.62,-0.24,-0.53,-0.53,-0.23,-0.23,-0.25,-0.07,NA,0.11,0.29,-0.54,-0.33,-0.21
P136181_1_ENSBTAG00000022991,-0.27507,-0.12,NA,-0.42,-0.01,-0.15,0.5465,-0.54,0.1782,0.1782,-0.42,0.6711,-0.23,0.4807,0.4807,-0.17,0.2977,0.3164,-0.41,0.09,0.29,0.16,-0.07,0.04,0.02
P134814_ENSBTAG00000006541,-0.4182,NA,NA,NA,-0.61,0.1221,0.2858,NA,NA,NA,NA,0.0309,NA,0.3838,0.3838,NA,NA,-0.02,NA,NA,0.14,NA,-0.13,0.19,-0.04
P133768_ENSBTAG00000021120,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
P138444_ENSBTAG00000000894,NA,NA,NA,0.0455,-0.25,NA,NA,-0.31,NA,0.5985,0.4818,NA,NA,NA,NA,-0.23,NA,-0.14,NA,NA,0.25,NA,NA,-0.30,NA
P138481_ENSBTAG00000005534,NA,NA,NA,0.1475,NA,NA,NA,0.1111,NA,0.2673,NA,NA,NA,NA,NA,NA,NA,-0.50,NA,NA,NA,NA,NA,0.10,NA
P111219_ENSBTAG00000004910,NA,NA,NA,NA,NA,0.5612,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,-0.09,-0.19,NA,NA,NA,NA,NA,NA,NA"
data1 <-read.table(text=data1,sep=",",header=T)

data2 <-"mirna,expression
mir-1,1506.554
mir-2,64.385
mir-3,790.762
mir-4,13.574
mir-5,59.737
mir-6,29832.972
mir-7,10085.201
mir-8,5.81
mir-9,53.09
mir-10,53.09
mir-11,13096.997
mir-12,561.459
mir-13,0.63
mir-14,57.918
mir-15,57.918
mir-16,0.695
mir-17,75.411
mir-18,258.793
mir-19,1.16
mir-20,3.95
mir-21,24.966
mir-22,31.509
mir-23,4.391111111
mir-24,16.659
mir-25,141.242"
data2 <-read.table(text=data2,sep=",",header=T)

Expected outcome:

data3 <- "P_G,mirna,expression
P111179_ENSBTAG00000005989,mir-8,5.81
P111179_ENSBTAG00000005989,mir-12,561.46
P111179_ENSBTAG00000005989,mir-13,0.63
P111179_ENSBTAG00000005989,mir-14,57.92
P111179_ENSBTAG00000005989,mir-17,75.41
P111179_ENSBTAG00000005989,mir-18,258.79
P111179_ENSBTAG00000005989,mir-24,16.66
P137378_ENSBTAG00000038920,mir-1,1506.55
P137378_ENSBTAG00000038920,mir-2,64.39
P137378_ENSBTAG00000038920,mir-4,13.57
P137378_ENSBTAG00000038920,mir-6,29832.97
P137378_ENSBTAG00000038920,mir-7,10085.20
P137378_ENSBTAG00000038920,mir-8,5.81
P137378_ENSBTAG00000038920,mir-9,53.09
P137378_ENSBTAG00000038920,mir-10,53.09
P137378_ENSBTAG00000038920,mir-11,13097.00
P137378_ENSBTAG00000038920,mir-13,0.63
P137378_ENSBTAG00000038920,mir-16,0.70
P137378_ENSBTAG00000038920,mir-19,1.16
P137378_ENSBTAG00000038920,mir-22,31.51
P137378_ENSBTAG00000038920,mir-25,141.24"
data3 <-read.table(text=data3,sep=",",header=T)

Answer 1

We can melt the first dataset and join on with the second dataset

library(data.table)
unique(setDT(data2)[melt(setDT(data1), id.var="P_G", na.rm = TRUE, variable.name = "mirna", 
   value.name = "expression")[,
   mirna:= sub("[.]", "-", mirna)
   ][expression>0], on = "mirna"][], by = c("mirna", "expression"))