What is the Human Cell Atlas?

From the Human Cell Atlas (HCA) website:

The cell is the core unit of the human body—the key to understanding the biology of health and the ways in which molecular dysfunction leads to disease. Yet our characterization of the hundreds of types and subtypes of cells in the human body is limited, based partly on techniques that have limited resolution and classifications that do not always map neatly to each other. Genomics has offered a systematic approach, but it has largely been applied in bulk to many cell types at once—masking critical differences between cells—and in isolation from other valuable sources of data.

Recent advances in single-cell genomic analysis of cells and tissues have put systematic, high-resolution and comprehensive reference maps of all human cells within reach. In other words, we can now realistically envision a human cell atlas to serve as a basis for both understanding human health and diagnosing, monitoring, and treating disease.

At its core, a cell atlas would be a collection of cellular reference maps, characterizing each of the thousands of cell types in the human body and where they are found. It would be an extremely valuable resource to empower the global research community to systematically study the biological changes associated with different diseases, understand where genes associated with disease are active in our bodies, analyze the molecular mechanisms that govern the production and activity of different cell types, and sort out how different cell types combine and work together to form tissues.

The Human Cell Atlas facilitates queries on it's data coordination platform with a RESTFUL API.

Installation

To install this package, use Bioconductor's BiocManager package.

if (!require("BiocManager"))
    install.packages("BiocManager")
BiocManager::install('HCABrowser')
library(HCABrowser)

Connecting to the Human Cell Atlas

The HCABrowser package relies on having network connectivety. Also, the HCA's Data Coordination Platform (DCP) must also be operational.

The HCABrowser object serves as the representation of the Human Cell Atlas. Upon creation, it will automatically peform a cursorary query and display a small table showing the first few bundles of the entire HCA. This intial table contains some columns that we have determined are most useful to users. The output also displays the url of the instance of the HCA DCP being used, the current query, whether bundles or files are being displayed, and the number of bundles in the results

By default, ten bundles per page will be displayed in the result and the default url to the HCA DCP will be used. Currently, the maximum number of bundles that can be shown per query is ten. These two values can be changed in the constructor.

If the HCA cannot be reached, an error will be thrown displaying the status of the request.

hca <- HCABrowser(url = 'https://dss.data.humancellatlas.org/v1', per_page = 10)
hca
## class: HCABrowser 
## Using hca-dcp at:
##   https://dss.data.humancellatlas.org/v1 
## 
## Current Query:
## 
## Current Selection:
##   "project_title", "project_short_name", "organ.text" 
## 
## class: SearchResult
##   bundle 1 - 10 of 543043
##   link: TRUE
## 
## Showing bundles with 10 results per page
## # A tibble: 10 x 5
##    bundle_fqid bundle_url project_json.pr… project_json.pr…
##    <fct>       <fct>      <chr>            <chr>           
##  1 ffffab51-b… https://d… <NA>             <NA>            
##  2 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  3 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  4 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  5 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  6 ffffa79b-9… https://d… <NA>             <NA>            
##  7 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
##  8 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
##  9 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
## 10 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
## # … with 1 more variable: specimen_from_organism_json.organ.text <chr>

Upon displaying the object, multiple fields can be seen:

The results tibble can be obtained using the results() method.

results(hca)
## # A tibble: 10 x 5
##    bundle_fqid bundle_url project_json.pr… project_json.pr…
##    <fct>       <fct>      <chr>            <chr>           
##  1 ffffab51-b… https://d… <NA>             <NA>            
##  2 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  3 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  4 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  5 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  6 ffffa79b-9… https://d… <NA>             <NA>            
##  7 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
##  8 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
##  9 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
## 10 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
## # … with 1 more variable: specimen_from_organism_json.organ.text <chr>

To toggle whether bundles or files are being displayed in the tibble, the activate() method can be used to choose which to display.

## Bundles are diaplyed be default
nrow(results(hca))
## [1] 10
## The HCABrowser object is activated here by 'files'
hca <- hca %>% activate('files')
hca
## class: HCABrowser 
## Using hca-dcp at:
##   https://dss.data.humancellatlas.org/v1 
## 
## Current Query:
## 
## Current Selection:
##   "project_title", "project_short_name", "organ.text" 
## 
## class: SearchResult
##   bundle 1 - 10 of 543043
##   link: TRUE
## 
## Showing files with 10 results per page
## # A tibble: 10 x 5
##    bundle_fqid bundle_url project_json.pr… project_json.pr…
##    <fct>       <fct>      <chr>            <chr>           
##  1 ffffab51-b… https://d… <NA>             <NA>            
##  2 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  3 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  4 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  5 ffffa79b-9… https://d… Tabula Muris     Tabula Muris: T…
##  6 ffffa79b-9… https://d… <NA>             <NA>            
##  7 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
##  8 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
##  9 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
## 10 fffeddc6-a… https://d… Tabula Muris     Tabula Muris: T…
## # … with 1 more variable: specimen_from_organism_json.organ.text <chr>
nrow(results(hca))
## [1] 10
## Revert back to showing bundles with 'bundles'
hca <- hca %>% activate('bundles')

To change how many pages are being displayed, the per_page() method can be used. (Note the hca dcp had a maximum of 10 bundles per page to be shown at a time)

#hca2 <- hca %>% per_page(n = 5)
#hca2

Since there are far more bundles in the HCA than can be shown, if link is True, the next set of bundles can be obtained using the nextResults method.

hca <- nextResults(hca)
hca
## class: HCABrowser 
## Using hca-dcp at:
##   https://dss.data.humancellatlas.org/v1 
## 
## Current Query:
## 
## Current Selection:
##   "project_title", "project_short_name", "organ.text" 
## 
## class: SearchResult
##   bundle 11 - 20 of 543043
##   link: TRUE
## 
## Showing bundles with 10 results per page
## # A tibble: 10 x 5
##    bundle_fqid bundle_url project_json.pr… project_json.pr…
##    <fct>       <fct>      <chr>            <chr>           
##  1 fffeddc6-a… https://d… <NA>             <NA>            
##  2 fffe6080-3… https://d… Tabula Muris     Tabula Muris: T…
##  3 fffe6080-3… https://d… Tabula Muris     Tabula Muris: T…
##  4 fffe6080-3… https://d… Tabula Muris     Tabula Muris: T…
##  5 fffe6080-3… https://d… Tabula Muris     Tabula Muris: T…
##  6 fffe6080-3… https://d… <NA>             <NA>            
##  7 fffd9cfe-6… https://d… Tabula Muris     Tabula Muris: T…
##  8 fffd9cfe-6… https://d… Tabula Muris     Tabula Muris: T…
##  9 fffd9cfe-6… https://d… Tabula Muris     Tabula Muris: T…
## 10 fffd9cfe-6… https://d… <NA>             <NA>            
## # … with 1 more variable: specimen_from_organism_json.organ.text <chr>

Querying the HCABrowser

To show which fields are available to query, use the supportedFilters() method.

hca <- HCABrowser()
hca %>% fields
## # A tibble: 394 x 2
##    abbreviated_names                   field_names                         
##    <chr>                               <chr>                               
##  1 address                             files.project_json.contributors.add…
##  2 alcohol_history                     files.donor_organism_json.medical_h…
##  3 analysis_file_json.describedBy      files.analysis_file_json.describedBy
##  4 analysis_file_json.file_core.file_… files.analysis_file_json.file_core.…
##  5 analysis_file_json.schema_type      files.analysis_file_json.schema_type
##  6 analysis_process_json.describedBy   files.analysis_process_json.describ…
##  7 analysis_process_json.schema_type   files.analysis_process_json.schema_…
##  8 analysis_protocol_json.describedBy  files.analysis_protocol_json.descri…
##  9 analysis_protocol_json.protocol_co… files.analysis_protocol_json.protoc…
## 10 analysis_protocol_json.schema_type  files.analysis_protocol_json.schema…
## # … with 384 more rows

The abbreviated_fields column indicates the shortest possible name that can be used to reference the field. The field_names columns shows the whole schema name on the json schema.

Availiable values to these fields can be found using the values() method. If the parameter fields is specified, it will display values related to those field. If not specified, the values for all fields will be shown.

hca %>% values(c('organ.text', 'library_construction_approach.text'))
## # A tibble: 23 x 2
##    field_names                                  value        
##    <fct>                                        <fct>        
##  1 files.specimen_from_organism_json.organ.text pancreas     
##  2 files.specimen_from_organism_json.organ.text tumor        
##  3 files.specimen_from_organism_json.organ.text embryo       
##  4 files.specimen_from_organism_json.organ.text lymph node   
##  5 files.specimen_from_organism_json.organ.text Brain        
##  6 files.specimen_from_organism_json.organ.text immune system
##  7 files.specimen_from_organism_json.organ.text blood        
##  8 files.specimen_from_organism_json.organ.text skin         
##  9 files.specimen_from_organism_json.organ.text skin of body 
## 10 files.specimen_from_organism_json.organ.text spleen       
## # … with 13 more rows

The HCA extends the functionality of the dplyr package's filter() and select() methods.

The filter() method allows the user to query the HCA by relating fields to certain values. Character fields can be queried using the operators:

Numeric fields can be queried with the operators:

Queries can be encompassed by parenthesese

Queries can be negated by placing the ! symbol in front

Combination operators can be used to combine queries

As an example, in order to find HCA resources associated with the brain. It can the be seen by looking at the result of the fields method, that organ.text can be used to reference files.specimen_from_organism.organ.text. Running organ.text through values, we see the following:

hca %>% values('organ.text')
## # A tibble: 15 x 2
##    field_names                                  value        
##    <fct>                                        <fct>        
##  1 files.specimen_from_organism_json.organ.text pancreas     
##  2 files.specimen_from_organism_json.organ.text tumor        
##  3 files.specimen_from_organism_json.organ.text embryo       
##  4 files.specimen_from_organism_json.organ.text lymph node   
##  5 files.specimen_from_organism_json.organ.text Brain        
##  6 files.specimen_from_organism_json.organ.text immune system
##  7 files.specimen_from_organism_json.organ.text blood        
##  8 files.specimen_from_organism_json.organ.text skin         
##  9 files.specimen_from_organism_json.organ.text skin of body 
## 10 files.specimen_from_organism_json.organ.text spleen       
## 11 files.specimen_from_organism_json.organ.text oesophagus   
## 12 files.specimen_from_organism_json.organ.text brain        
## 13 files.specimen_from_organism_json.organ.text kidney       
## 14 files.specimen_from_organism_json.organ.text "bone "      
## 15 files.specimen_from_organism_json.organ.text bone

Now we see that “brain” and “Brain” are available values. Since these values are the result of input by other users, there may be errors or inconsistencies. To be safe, both fields can be queried with the following query:

hca2 <- hca %>% filter(organ.text == c('Brain', 'brain'))
hca2 <- hca %>% filter(organ.text %in% c('Brain', 'brain'))
hca2 <- hca %>% filter(organ.text == Brain | organ.text == brain)
hca2
## class: HCABrowser 
## Using hca-dcp at:
##   https://dss.data.humancellatlas.org/v1 
## 
## Current Query:
##   organ.text == Brain | organ.text == brain 
## 
## Current Selection:
##   "project_title", "project_short_name", "organ.text" 
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.organ.text" 
## 
## class: SearchResult
##   bundle 1 - 10 of 81338
##   link: TRUE
## 
## Showing bundles with 10 results per page
## # A tibble: 10 x 5
##    project_json.pr… project_json.pr… specimen_from_o… bundle_fqid
##    <chr>            <chr>            <chr>            <fct>      
##  1 Tabula Muris     Tabula Muris: T… brain            fffca6d1-b…
##  2 Tabula Muris     Tabula Muris: T… brain            fffca6d1-b…
##  3 Tabula Muris     Tabula Muris: T… brain            fffca6d1-b…
##  4 Tabula Muris     Tabula Muris: T… brain            fffca6d1-b…
##  5 1M Neurons       1.3 Million Bra… Brain            fffb06c9-8…
##  6 Tabula Muris     Tabula Muris: T… brain            fffa56eb-0…
##  7 Tabula Muris     Tabula Muris: T… brain            fffa56eb-0…
##  8 Tabula Muris     Tabula Muris: T… brain            fffa56eb-0…
##  9 Tabula Muris     Tabula Muris: T… brain            fffa56eb-0…
## 10 Tabula Muris     Tabula Muris: T… brain            fff9e14c-b…
## # … with 1 more variable: bundle_url <fct>

If we also wish to search for results based on the NCBI Taxon ID for human, 9606, as well as brain, we can perform this query in a variety of ways.

hca2 <- hca %>% filter(organ.text %in% c('Brain', 'brain')) %>%
                filter('specimen_from_organism_json.biomaterial_core.ncbi_taxon_id' == 9606)
hca2 <- hca %>% filter(organ.text %in% c('Brain', 'brain'),
                       'specimen_from_organism_json.biomaterial_core.ncbi_taxon_id' == 9606)
hca <- hca %>% filter(organ.text %in% c('Brain', 'brain') &
                      'specimen_from_organism_json.biomaterial_core.ncbi_taxon_id' == 9606)
hca
## class: HCABrowser 
## Using hca-dcp at:
##   https://dss.data.humancellatlas.org/v1 
## 
## Current Query:
##   organ.text %in% c("Brain", "brain") & "specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" == 9606 
## 
## Current Selection:
##   "project_title", "project_short_name", "organ.text" 
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" 
## 
## class: SearchResult
##   bundle 1 - 1 of 1
##   link: FALSE
## 
## Showing bundles with 10 results per page
## # A tibble: 1 x 6
##   project_json.pr… project_json.pr… specimen_from_o… specimen_from_o…
##   <chr>            <chr>            <chr>            <chr>           
## 1 10x_prod_test_0… 10x_prod_test_0… 9606             brain           
## # … with 2 more variables: bundle_fqid <fct>, bundle_url <fct>

The HCABrowser package is able to handle arbitrarily complex queries on the Human Cell Atlas.

hca2 <- hca %>% filter((!organ.text %in% c('Brain', 'blood')) & 
                       (files.specimen_from_organism_json.genus_species.text == "Homo sapiens" |
                        library_preparation_protocol_json.library_construction_approach.text == 'Smart-seq2')
                )
hca2
## class: HCABrowser 
## Using hca-dcp at:
##   https://dss.data.humancellatlas.org/v1 
## 
## Current Query:
##   organ.text %in% c("Brain", "brain") & "specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" == 9606 
##   (!organ.text %in% c("Brain", "blood")) & (files.specimen_from_organism_json.genus_species.text == "Homo sapiens" | library_preparation_protocol_json.library_construction_approach.text == "Smart-seq2") 
## 
## Current Selection:
##   "project_title", "project_short_name", "organ.text" 
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" 
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.biomaterial_core.ncbi_taxon_id",
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.genus_species.text",
##   "files.library_preparation_protocol_json.library_construction_approach.text" 
## 
## class: SearchResult
##   bundle 0 - 0 of 0
##   link: FALSE
## 
## Showing bundles with 10 results per page
## # A tibble: 0 x 0

The HCABrowser object can undo the most recent queries run on it.

hca <- hca %>% filter(organ.text == heart)
hca <- hca %>% filter(organ.text != brain)
hca <- hca %>% undoEsQuery(n = 2)
hca
## class: HCABrowser 
## Using hca-dcp at:
##   https://dss.data.humancellatlas.org/v1 
## 
## Current Query:
##   organ.text %in% c("Brain", "brain") & "specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" == 9606 
## 
## Current Selection:
##   "project_title", "project_short_name", "organ.text" 
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" 
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" 
## 
## class: SearchResult
##   bundle 1 - 1 of 1
##   link: FALSE
## 
## Showing bundles with 10 results per page
## # A tibble: 1 x 6
##   project_json.pr… project_json.pr… specimen_from_o… specimen_from_o…
##   <chr>            <chr>            <chr>            <chr>           
## 1 10x_prod_test_0… 10x_prod_test_0… 9606             brain           
## # … with 2 more variables: bundle_fqid <fct>, bundle_url <fct>

If one would want to start from a fresh query but retain the modifications made to the HCABrowser object, the resetEsQuery() method can be used.

hca <- hca %>% resetEsQuery
hca

Using fields(), we can find that the fields paired_end and organ.ontology are availiable. These fields can be shown in our resulting HCABrowser object using the select() method.

hca2 <- hca %>% select('paired_end', 'organ.ontology')
#hca2 <- hca %>% select(paired_end, organ.ontology)
hca2 <- hca %>% select(c('paired_end', 'organ.ontology'))
hca2
## class: HCABrowser 
## Using hca-dcp at:
##   https://dss.data.humancellatlas.org/v1 
## 
## Current Query:
##   organ.text %in% c("Brain", "brain") & "specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" == 9606 
## 
## Current Selection:
##   "project_title", "project_short_name", "organ.text" 
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" 
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" 
##   "paired_end", "organ.ontology" 
## 
## class: SearchResult
##   bundle 1 - 1 of 1
##   link: FALSE
## 
## Showing bundles with 10 results per page
## # A tibble: 1 x 8
##   project_json.pr… project_json.pr… sequencing_prot… specimen_from_o…
##   <chr>            <chr>            <lgl>            <chr>           
## 1 10x_prod_test_0… 10x_prod_test_0… FALSE            9606            
## # … with 4 more variables:
## #   specimen_from_organism_json.organ.ontology <chr>,
## #   specimen_from_organism_json.organ.text <chr>, bundle_fqid <fct>,
## #   bundle_url <fct>

Finally, instead of a using the filter and select methods, one can query the Human Cell Atlas by using a json query and the postSearch() method. Note that unabbreviated names must be used for these kinds of queries.

Obtaining results from the HCABrowser object

Once the user is satisfied with their query, the results() method can be used to create a tibble of the first n bundles in the search. Note that since the maximum page size is 10, the method will need to make multiple requests to the hca dcp. This may take some time for large requests.

res <- hca %>% results(n = 36)
res
## # A tibble: 9 x 6
##   project_json.pr… project_json.pr… specimen_from_o… specimen_from_o…
##   <chr>            <chr>            <chr>            <chr>           
## 1 10x_prod_test_0… 10x_prod_test_0… 9606             brain           
## 2 10x_prod_test_0… 10x_prod_test_0… 9606             brain           
## 3 10x_prod_test_0… 10x_prod_test_0… 9606             brain           
## 4 10x_prod_test_0… 10x_prod_test_0… 9606             brain           
## 5 <NA>             <NA>             <NA>             <NA>            
## 6 <NA>             <NA>             <NA>             <NA>            
## 7 <NA>             <NA>             <NA>             <NA>            
## 8 <NA>             <NA>             <NA>             <NA>            
## 9 <NA>             <NA>             <NA>             <NA>            
## # … with 2 more variables: bundle_fqid <fct>, bundle_url <fct>

One can also simply pull bundles from the HCABrowser object's results.

bundle_fqids <- hca %>% pullBundles(n = 1)
bundle_fqids
## [1] "f4151752-478a-4742-8977-dd44fe027bfb.2019-01-08T223501.790366Z"

One can query using just the bundle fqids by using the showBundles method.

hca <- hca %>% showBundles(bundle_fqids = bundle_fqids)
hca
## class: HCABrowser 
## Using hca-dcp at:
##   https://dss.data.humancellatlas.org/v1 
## 
## Current Query:
##   organ.text %in% c("Brain", "brain") & "specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" == 9606 
##   "uuid" %in% bundle_fqids 
## 
## Current Selection:
##   "project_title", "project_short_name", "organ.text" 
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" 
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.biomaterial_core.ncbi_taxon_id" 
##   "files.specimen_from_organism_json.organ.text",
##   "files.specimen_from_organism_json.biomaterial_core.ncbi_taxon_id",
##   "uuid" 
## 
## class: SearchResult
##   bundle 1 - 1 of 1
##   link: FALSE
## 
## Showing bundles with 10 results per page
## # A tibble: 1 x 6
##   project_json.pr… project_json.pr… specimen_from_o… specimen_from_o…
##   <chr>            <chr>            <chr>            <chr>           
## 1 10x_prod_test_0… 10x_prod_test_0… 9606             brain           
## # … with 2 more variables: bundle_fqid <fct>, bundle_url <fct>
sessionInfo()
## R version 3.6.0 (2019-04-26)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 18.04.2 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.9-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.9-bioc/R/lib/libRlapack.so
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] HCABrowser_1.0.0 dplyr_0.8.0.1    BiocStyle_2.12.0 knitr_1.22      
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.1          plyr_1.8.4          googleAuthR_0.7.0  
##  [4] pillar_1.3.1        compiler_3.6.0      BiocManager_1.30.4 
##  [7] dbplyr_1.4.0        tools_3.6.0         digest_0.6.18      
## [10] bit_1.1-14          jsonlite_1.6        BiocFileCache_1.8.0
## [13] RSQLite_2.1.1       evaluate_0.13       memoise_1.1.0      
## [16] tibble_2.1.1        pkgconfig_2.0.2     rlang_0.3.4        
## [19] igraph_1.2.4.1      tidygraph_1.1.2     cli_1.1.0          
## [22] DBI_1.0.0           curl_3.3            yaml_2.2.0         
## [25] parallel_3.6.0      xfun_0.6            stringr_1.4.0      
## [28] httr_1.4.0          hms_0.4.2           S4Vectors_0.22.0   
## [31] rappdirs_0.3.1      stats4_3.6.0        bit64_0.9-7        
## [34] tidyselect_0.2.5    glue_1.3.1          R6_2.4.0           
## [37] fansi_0.4.0         rmarkdown_1.12      tidyr_0.8.3        
## [40] readr_1.3.1         purrr_0.3.2         blob_1.1.1         
## [43] magrittr_1.5        htmltools_0.3.6     BiocGenerics_0.30.0
## [46] assertthat_0.2.1    utf8_1.1.4          stringi_1.4.3      
## [49] crayon_1.3.4

Developer notes