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Structure
The term matching table contains links to the information needed to
create the output table. Some general term matching tables can be
created by the function create_term_matching_table()
by specifying the
used instruments and the origin key.
This function falls back on the included list of data frames tmt_list
where each table is designed to fit one instrument. By calling the
function with only one instrument name it will just extract the specific
data frame. If called with more than one instrument (ordinarily 2) it
will bind the tables together.
tmt_LC_pump <- create_term_match_table(
instrument_list = c("Thermo EASY-nLC"))
# no origin key set
The table always consists of 6 columns whose order is important. The count of rows differ depending on the choosen requirements and the type of instrument.
colnames(tmt_LC_pump)
#> [1] "term" "term_verbose" "origin" "handle_type"
#> [5] "handle" "example"
The first column of the resulting table is always the term
. It is a
short and unique description of the row. While the second,
term_verbose
contains a more detailed and readable title.
knitr::kable(tmt_LC_pump[1:2])
term | term_verbose |
---|---|
hplc_instrument | High Performance Liquid Chromatography (HPLC) Instrument |
hplc_vendor | HPLC Vendor |
hplc_model | HPLC Model |
hplc_column | Chromatography Column |
hplc_mobilephases | Chromatography Mobile Phases |
hplc_samplevolume | Injected Sample Volume |
hplc_gradient | Chromatography Gradient |
The third collumn origin
contains keys determining which requirements
to satisfy. These keys were read in the function
create_term_matching_table()
and compared to the value of
origin_key
.
knitr::kable(tmt_LC_pump[3])
origin |
---|
author;miape;jpr_guidelines_ms |
author;miape;jpr_guidelines_ms |
author;miape;jpr_guidelines_ms |
author;miape;jpr_guidelines_ms |
author;miape;jpr_guidelines_ms |
author;miape |
author;miape;jpr_guidelines_ms |
In the fourth column handle_type
specifys how to interpret the fifth
column handle
. "list_path"
indicates that handle
is a path in the
flattened json. "literal"
leads to just copy the value of handle
.
With "parameter" the row stays empty because the information is not
represented in the json.
knitr::kable(tmt_LC_pump[4:5])
handle_type | handle |
---|---|
list_path | Instruments.Thermo EASY-nLC.InstrumentFriendName |
literal | Thermo Scientific |
parameter | NA |
parameter | NA |
parameter | NA |
list_path | Instruments.Thermo EASY-nLC.Method.Sample pickup.Volume [µl] |
function | document_easy_nlc_gradient |
The last column shows an example of which value the row could have.
knitr::kable(tmt_LC_pump[c(2,6)])
term_verbose | example |
---|---|
High Performance Liquid Chromatography (HPLC) Instrument | Thermo EASY-nLC |
HPLC Vendor | Thermo Scientific |
HPLC Model | NA |
Chromatography Column | NA |
Chromatography Mobile Phases | NA |
Injected Sample Volume | 4.00 |
Chromatography Gradient | NA |
See Creation.