From https://support.bioconductor.org/p/9138939/.
library(GenomicDataCommons,quietly = TRUE)
I made a small change to the filtering expression approach based on
changes to lazy evaluation best practices. There is now no need to
include the ~
in the filter expression. So:
q = files() %>%
GenomicDataCommons::filter(
cases.project.project_id == 'TCGA-COAD' &
data_type == 'Aligned Reads' &
experimental_strategy == 'RNA-Seq' &
data_format == 'BAM')
And get a count of the results:
count(q)
## [1] 521
And the manifest.
manifest(q)
## Rows: 521 Columns: 5
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (4): id, filename, md5, state
## dbl (1): size
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Your question about race and ethnicity is a good one.
all_fields = available_fields(files())
And we can grep for race
or ethnic
to get potential matching fields
to look at.
grep('race|ethnic',all_fields,value=TRUE)
## [1] "cases.demographic.ethnicity"
## [2] "cases.demographic.race"
## [3] "cases.follow_ups.hormonal_contraceptive_type"
## [4] "cases.follow_ups.hormonal_contraceptive_use"
## [5] "cases.follow_ups.scan_tracer_used"
Now, we can check available values for each field to determine how to complete our filter expressions.
available_values('files',"cases.demographic.ethnicity")
## [1] "not hispanic or latino" "not reported" "hispanic or latino"
## [4] "unknown" "not allowed to collect" "_missing"
available_values('files',"cases.demographic.race")
## [1] "white"
## [2] "not reported"
## [3] "black or african american"
## [4] "asian"
## [5] "unknown"
## [6] "other"
## [7] "not allowed to collect"
## [8] "american indian or alaska native"
## [9] "native hawaiian or other pacific islander"
## [10] "_missing"
We can complete our filter expression now to limit to white
race only.
q_white_only = q %>%
GenomicDataCommons::filter(cases.demographic.race=='white')
count(q_white_only)
## [1] 249
manifest(q_white_only)
## Rows: 249 Columns: 5
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (4): id, filename, md5, state
## dbl (1): size
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
GenomicDataCommons
?I would like to get the number of cases added (created, any logical datetime would suffice here) to the TCGA project by experiment type. I attempted to get this data via GenomicDataCommons package, but it is giving me I believe the number of files for a given experiment type rather than number cases. How can I get the number of cases for which there is RNA-Seq data?
library(tibble)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:GenomicDataCommons':
##
## count, filter, select
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(GenomicDataCommons)
cases() %>%
GenomicDataCommons::filter(~ project.program.name=='TCGA' &
files.experimental_strategy=='RNA-Seq') %>%
facet(c("files.created_datetime")) %>%
aggregations() %>%
.[[1]] %>%
as_tibble() %>%
dplyr::arrange(dplyr::desc(key))