Getting Started with dafr • dafr

What is a Daf?

A Daf (Data Axes Format) is a multi-axis container for biological / scientific data. Think of it as a typed dictionary of scalars, per-axis vectors, and per-axis-pair matrices, with cache invalidation and lazy mmap-backed reads.

Create a Daf

d <- memory_daf(name = "demo")
add_axis(d, "cell", c("c1", "c2", "c3"))
add_axis(d, "gene", c("g1", "g2"))
set_scalar(d, "organism", "human")
set_vector(d, "cell", "donor", c("A", "B", "A"))
set_matrix(d, "cell", "gene", "UMIs",
           matrix(1:6, nrow = 3, ncol = 2))
print(d)
#> <dafr::MemoryDaf>
#>  @ name                  : chr "demo"
#>  @ internal              :<environment: 0x560478b5bbf8> 
#>  @ cache                 :<environment: 0x560478b79230> 
#>  @ axis_version_counter  :<environment: 0x560478b7d6c8> 
#>  @ vector_version_counter:<environment: 0x560478b7d3f0> 
#>  @ matrix_version_counter:<environment: 0x560478b7d118>

Reading data

get_scalar(d, "organism")
#> [1] "human"
get_vector(d, "cell", "donor")
#>  c1  c2  c3 
#> "A" "B" "A"
get_matrix(d, "cell", "gene", "UMIs")
#>    g1 g2
#> c1  1  4
#> c2  2  5
#> c3  3  6

Queries

Queries let you compose reads. Two equivalent forms — a string DSL and pipe-chain builders:

get_query(d, "@ cell : donor")
#>  c1  c2  c3 
#> "A" "B" "A"
get_query(d, ". organism")
#> [1] "human"

d[Axis("cell") |> LookupVector("donor")]
#>  c1  c2  c3 
#> "A" "B" "A"

Data frames

get_dataframe(d, "cell")
#>    donor
#> c1     A
#> c2     B
#> c3     A

Persistence

# Write to a directory:
fd <- files_daf(tempfile("dafr-"), mode = "w+", name = "persisted")
copy_all(d, fd)

Example data

d2 <- example_cells_daf()
axes_set(d2)
#> [1] "cell"       "donor"      "experiment" "gene"