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lines changed Original file line number Diff line number Diff line change @@ -34,9 +34,7 @@ Explore the HCA content
3434
3535``` {r}
3636get_metadata() |>
37- distinct(tissue, file_id) |>
38- count(tissue) |>
39- arrange(desc(n))
37+ distinct(tissue, file_id)
4038```
4139
4240Query raw counts
@@ -45,7 +43,7 @@ Query raw counts
4543library(stringr)
4644sce <-
4745 get_metadata() |>
48- filter(
46+ dplyr:: filter(
4947 ethnicity == "African" &
5048 str_like(assay, "%10x%") &
5149 tissue == "lung parenchyma" &
@@ -61,7 +59,7 @@ Query counts scaled per million. This is helpful if just few genes are of intere
6159``` {r}
6260sce <-
6361 get_metadata() |>
64- filter(
62+ dplyr:: filter(
6563 ethnicity == "African" &
6664 str_like(assay, "%10x%") &
6765 tissue == "lung parenchyma" &
@@ -76,7 +74,7 @@ Extract only a subset of genes:
7674
7775``` {r}
7876get_metadata() |>
79- filter(
77+ dplyr:: filter(
8078 ethnicity == "African" &
8179 str_like(assay, "%10x%") &
8280 tissue == "lung parenchyma" &
@@ -89,14 +87,15 @@ Extract the counts as a Seurat object:
8987
9088``` {r}
9189get_metadata() |>
92- filter(
90+ dplyr:: filter(
9391 ethnicity == "African" &
9492 str_like(assay, "%10x%") &
9593 tissue == "lung parenchyma" &
9694 str_like(cell_type, "%CD4%")
9795 ) |>
9896 get_seurat()
9997```
98+
10099``` {r}
101100sessionInfo()
102101```
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