Thanks Dr. Gatto... I figured as much.  I have a Shiny app that, after converting raw -> mzXML will allow creating spectral databases. So I'm interfacing an RSQLite database component now but lose provenance of the original raw files. (Maybe there's a way to directly serialize the mzXMl directly into a SQL blob from R?)

As for a PR- if you could point to the appropriate GH file(s) I can take a look if it's something I could help with.

Thanks!

RSQLite Code:

Access previously created RSQLite database

newDatabase <- DBI::dbConnect(RSQLite::SQLite(), paste0("SpectraLibrary/", "example", ".sqlite"))
db          <- dplyr::tbl(newDatabase, "IDBacDatabase")

db %>% dplyr::select(c(1,11:19)) %>% dplyr::select(-c(6,7)) #remove user-input-metadata columns

## # Source:   lazy query [?? x 8]
## # Database: sqlite 3.22.0
## #   [C:\Users\chase\Documents\GitHub\IDBac_App\inst\app\SpectraLibrary\example.sqlite]
##    Strain_ID    manufacturer  model  ionisation  analyzer Small_Molecule_~
##    <chr>        <chr>         <chr>  <chr>       <chr>               <int>
##  1 114A-2       Bruker Dalto~ Bruke~ matrix-ass~ time-of~               NA
## # ... with more rows, and 2 more variables: mzXML <blob>, rds <blob>

db %>% dplyr::select(c(1,18,19))

## # Source:   lazy query [?? x 3]
## # Database: sqlite 3.22.0
## #   [C:\Users\chase\Documents\GitHub\IDBac_App\inst\app\SpectraLibrary\example.sqlite]
##    Strain_ID                                               mzXML       rds
##    <chr>                                                  <blob>    <blob>
##  1 114A-2                                         <raw  7.14 MB> <raw 1 B>
## # ... with more rows

Display what used to be a mzXML file (that held 6 spectra)

oneSpec <- db %>% dplyr::filter(Strain_ID == "114A-2") %>% dplyr::select(mzXML) %>% dplyr::collect()
mzAccess <- lapply(oneSpec[[1]], function(x) memDecompress(x,type="gzip"))
mzAccess <- sapply(mzAccess, function(x) unserialize(x, NULL))

lapply(q3[[1]], function(x) dplyr::as_tibble(data.frame(x)))

## [[1]]
## # A tibble: 42,154 x 2
##       X1    X2
##    <dbl> <dbl>
##  1 1920. 36161
##  2 1920. 36226
##  3 1920. 36373
##  4 1921. 36579
##  5 1921. 36741
##  6 1921. 36738
##  7 1921. 36741
##  8 1922. 36878
##  9 1922. 37068
## 10 1922. 37028
## # ... with 42,144 more rows
## 
## [[2]]
## # A tibble: 253,781 x 2
##       X1    X2
##    <dbl> <dbl>
##  1  59.6     9
##  2  59.6     7
##  3  59.6     7
##  4  59.6    16
##  5  59.6    13
##  6  59.6    10
##  7  59.6    18
##  8  59.6    14
##  9  59.6     4
## 10  59.7    12
## # ... with 253,771 more rows
## 
## [[3]]
## # A tibble: 42,154 x 2
##       X1    X2
##    <dbl> <dbl>
##  1 1920. 18932
##  2 1920. 18886
##  3 1920. 18839
##  4 1921. 18796
##  5 1921. 18869
##  6 1921. 19063
##  7 1921. 18915
##  8 1922. 19000
##  9 1922. 19058
## 10 1922. 19000
## # ... with 42,144 more rows
## 
## [[4]]
## # A tibble: 253,781 x 2
##       X1    X2
##    <dbl> <dbl>
##  1  59.6    15
##  2  59.6    11
##  3  59.6    11
##  4  59.6    26
##  5  59.6    19
##  6  59.6    18
##  7  59.6     7
##  8  59.6    18
##  9  59.6    12
## 10  59.7    11
## # ... with 253,771 more rows
## 
## [[5]]
## # A tibble: 253,781 x 2
##       X1    X2
##    <dbl> <dbl>
##  1  59.6    10
##  2  59.6    22
##  3  59.6    18
##  4  59.6    12
##  5  59.6     6
##  6  59.6     8
##  7  59.6     7
##  8  59.6    15
##  9  59.6    13
## 10  59.7    10
## # ... with 253,771 more rows
## 
## [[6]]
## # A tibble: 42,154 x 2
##       X1    X2
##    <dbl> <dbl>
##  1 1920. 32558
##  2 1920. 32717
##  3 1920. 32893
##  4 1921. 33004
##  5 1921. 33049
##  6 1921. 33296
##  7 1921. 33363
##  8 1922. 33543
##  9 1922. 33828
## 10 1922. 33820
## # ... with 42,144 more rows