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Source  : 2fa80f3
Branch  : main
Author  : Andrew Ghazi <[email protected]>
Time    : 2024-10-07 18:41:12 +0000
Message : Merge pull request #56 from ccb-hms/chimera_bg

background on chimera
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actions-user committed Oct 7, 2024
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7 changes: 6 additions & 1 deletion intro-sce.md
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Expand Up @@ -132,7 +132,9 @@ There are two main disadvantages to this "from-scratch" approach:

::::

Let's look at an example dataset. `WTChimeraData` comes from a study on mouse development. We can assign one sample to a `SingleCellExperiment` object named `sce` like so:
Let's look at an example dataset. `WTChimeraData` comes from a study on mouse development [Pijuan-Sala et al.](https://www.nature.com/articles/s41586-019-0933-9). The study profiles the effect of a transcription factor TAL1 and its influence on mouse development. Because mutations in this gene can cause severe developmental issues, Tal1-/- cells (positive for tdTomato, a fluorescent protein) were injected into wild-type blastocysts (tdTomato-), forming chimeric embryos.

We can assign one sample to a `SingleCellExperiment` object named `sce` like so:


``` r
Expand Down Expand Up @@ -422,4 +424,7 @@ altExpNames(0):

::::::::::::::::::::::::::::::::::::::::::::::::

## References

1. Pijuan-Sala B, Griffiths JA, Guibentif C et al. (2019). A single-cell molecular map of mouse gastrulation and early organogenesis. Nature 566, 7745:490-495.

35 changes: 17 additions & 18 deletions large_data.md
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Expand Up @@ -438,21 +438,22 @@ table(exact = colLabels(sce), approx = clusters)

``` output
approx
exact 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1 90 0 0 0 1 0 0 0 1 0 0 0 0 0 0
2 0 143 0 0 0 0 0 0 0 0 0 0 0 0 1
3 0 0 75 0 2 0 0 0 0 0 0 0 0 0 0
4 0 0 0 341 0 0 0 0 0 0 0 0 0 0 56
5 0 0 0 0 392 0 0 1 0 1 0 0 0 0 0
6 0 0 0 0 0 79 131 0 0 0 0 0 0 0 0
7 0 0 0 0 0 245 0 0 0 1 0 0 0 0 0
8 0 0 0 0 0 0 0 95 0 0 0 0 0 0 0
9 1 0 0 0 2 0 0 0 106 0 0 0 0 0 0
10 0 0 0 0 0 0 0 0 0 105 0 0 0 0 0
11 0 0 0 0 0 0 1 0 0 5 147 0 0 0 0
12 0 0 0 0 1 0 0 0 0 23 0 199 0 0 0
13 0 0 0 0 0 0 0 0 0 0 0 0 146 0 0
14 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0
exact 1 2 3 4 5 6 7 8 9 10 11 12 13 14
1 88 0 0 0 0 0 0 2 0 0 0 0 0 0
2 0 86 0 0 0 0 0 0 0 0 0 0 0 0
3 0 57 75 1 0 0 0 0 0 0 0 1 0 0
4 0 0 0 341 0 0 0 0 0 0 0 0 0 0
5 0 0 0 0 176 0 0 0 0 0 0 11 0 0
6 0 0 0 0 0 73 128 0 0 1 0 0 0 0
7 0 0 0 0 0 253 0 0 1 0 0 0 0 0
8 1 0 0 0 0 0 0 106 0 0 0 1 0 0
9 0 0 0 0 0 0 0 0 113 0 10 0 0 0
10 0 0 0 0 0 0 0 0 0 153 0 0 0 0
11 0 0 0 0 0 0 0 0 0 0 198 0 0 0
12 0 0 0 0 0 0 0 0 1 0 0 312 0 0
13 0 0 0 0 0 0 0 0 0 0 0 0 146 0
14 0 0 0 0 0 0 0 0 0 0 0 0 0 20
15 0 0 0 56 0 0 0 0 0 0 0 0 0 0
```

The similarity of the two clusterings can be quantified by calculating the pairwise Rand index:
Expand Down Expand Up @@ -926,7 +927,7 @@ loaded via a namespace (and not attached):
[131] spatstat.geom_3.2-9 RcppHNSW_0.6.0
[133] reshape2_1.4.4 ScaledMatrix_1.12.0
[135] BiocVersion_3.19.1 evaluate_0.23
[137] renv_1.0.9 BiocManager_1.30.23
[137] renv_1.0.10 BiocManager_1.30.23
[139] httpuv_1.6.15 RANN_2.6.1
[141] tidyr_1.3.1 purrr_1.0.2
[143] polyclip_1.10-6 future_1.33.2
Expand Down Expand Up @@ -1065,5 +1066,3 @@ system.time({i.out <- runPCA(sce.brain,
- Converter functions between existing single-cell data formats enable analysis workflows that leverage complementary functionality from poplular single-cell analysis ecosystems.

::::::::::::::::::::::::::::::::::::::::::::::::

## References
4 changes: 2 additions & 2 deletions md5sum.txt
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Expand Up @@ -4,11 +4,11 @@
"config.yaml" "b0d664d3d6abdd0e98b16282e1c03107" "site/built/config.yaml" "2024-09-24"
"index.md" "1a5a4a9032969ed06a606ba9cba366b1" "site/built/index.md" "2024-10-04"
"links.md" "8184cf4149eafbf03ce8da8ff0778c14" "site/built/links.md" "2024-09-24"
"episodes/intro-sce.Rmd" "bab83b985793d568bb9a6173d6080038" "site/built/intro-sce.md" "2024-10-04"
"episodes/intro-sce.Rmd" "4403772aa3b476575ca795b48f04e4f4" "site/built/intro-sce.md" "2024-10-07"
"episodes/eda_qc.Rmd" "d1a9a8a578fff2b0e9566ec613da388d" "site/built/eda_qc.md" "2024-10-03"
"episodes/cell_type_annotation.Rmd" "8fab6e0cbb60d6fe6a67a0004c5ce5ab" "site/built/cell_type_annotation.md" "2024-10-02"
"episodes/multi-sample.Rmd" "6d47bd1941b7a83000873da8d836fba0" "site/built/multi-sample.md" "2024-10-04"
"episodes/large_data.Rmd" "ba9660bc24664972f540bbe5fdc34d08" "site/built/large_data.md" "2024-10-04"
"episodes/large_data.Rmd" "e3295a682af24d014423fa82b3f70e6e" "site/built/large_data.md" "2024-10-07"
"episodes/hca.Rmd" "1577de2f4a851c7e99e3a8459230d6f1" "site/built/hca.md" "2024-10-04"
"instructors/instructor-notes.md" "205339793f625a1844a768dea8e4a9c8" "site/built/instructor-notes.md" "2024-09-24"
"learners/reference.md" "40fc1d0be2412d2d9d434a5bc84e4de8" "site/built/reference.md" "2024-09-24"
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