Combining columns, update columns based on other df, fill NAs

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at the beginning I'd like to note that I found multiple solutions on SO but none of them met my expectations.

I have to DF's:

1.

E                           F              G        H
chr1_100203723_100203724    NA             NA       NA
chr1_100212951_100212952    rs760764323    A,G,     0.000008,0.999992,
chr1_10032235_10032236      NA             NA       NA
chr1_100327060_100327061    NA             NA       NA
chr1_100346889_100346890    NA             NA       NA
chr1_100347237_100347238    rs749372877    C,G,T,   0.000008,0.000008,0.999983,
chr1_100357190_100357191    NA             NA       NA
chr1_100358057_100358058    NA             NA       NA
chr2_182852606_182852607    NA             NA       NA
chr2_202492077_202492078    NA             NA       NA
chr2_203760838_203760839    NA             NA       NA
chr2_215976351_215976352    NA             NA       NA
chr2_220354644_220354645    NA             NA       NA
chr2_234749403_234749404    NA             NA       NA
chr2_11802110_11802111      NA             NA       NA
chr2_31167747_31167748      NA             NA       NA

2.

E                           F               G       H
chr1_100203723_100203724    NA              NA      NA
chr1_100212951_100212952    NA              NA      NA
chr1_10032235_10032236      NA              NA      NA
chr1_100327060_100327061    NA              NA      NA
chr1_100346889_100346890    NA              NA      NA
chr1_100347237_100347238    NA              NA      NA
chr1_100357190_100357191    NA              NA      NA
chr1_100358057_100358058    NA              NA      NA
chr2_182852606_182852607    rs773426830     C,T,    0.999967,0.000033,
chr2_202492077_202492078    rs750583431     C,G,    0.000013,0.999987,
chr2_203760838_203760839    NA              NA      NA
chr2_215976351_215976352    rs113648834     C,T,    0.999934,0.000066,
chr2_220354644_220354645    NA              NA      NA
chr2_234749403_234749404    NA              NA      NA
chr2_11802110_11802111      rs371327070     A,G,    0.000044,0.999956,
chr2_31167747_31167748      rs201375957     A,C,T,  0.000008,0.999887,0.000105,

Desired output:

E                           F               G       H
chr1_100203723_100203724    NA              NA      NA
chr1_100212951_100212952    rs760764323     A,G,    0.000008,0.999992,
chr1_10032235_10032236      NA              NA      NA
chr1_100327060_100327061    NA              NA      NA
chr1_100346889_100346890    NA              NA      NA
chr1_100347237_100347238    rs749372877     C,G,T,  0.000008,0.000008,0.999983,
chr1_100357190_100357191    NA              NA      NA
chr1_100358057_100358058    NA              NA      NA
chr2_182852606_182852607    rs773426830     C,T,    0.999967,0.000033,
chr2_202492077_202492078    rs750583431     C,G,    0.000013,0.999987,
chr2_203760838_203760839    NA              NA      NA
chr2_215976351_215976352    rs113648834     C,T,    0.999934,0.000066,
chr2_220354644_220354645    NA              NA      NA
chr2_234749403_234749404    NA              NA      NA
chr2_11802110_11802111      rs371327070     A,G,    0.000044,0.999956,
chr2_31167747_31167748      rs201375957     A,C,T,  0.000008,0.999887,0.000105,

As you see DF1 is updated by DF2 columns F, G, H, where column E is my unique index. I tried to do merge() but this function didin't update my rows, it jus added columns of DF2 to DF1. I also tried updating with data.table and tidyverse, and my rows have been updated but other ones went to NAs... Finally I decided to do simple lapply() with nested ifelse(), however I don't know how to update all three columns simultaneously, what is more this is terrible slow for my over 50000 rows of data in each DF...

What I did so far:

DF1$F <- sapply(1:nrow(DF1), function(i) ifelse(DF1[i,1]==DF2[i,1] & is.na(DF1[i,1]), DF2[i,1], DF[i,1]))
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