diff --git a/assets/slides.html b/assets/slides.html index ff44f3d..32621e5 100644 --- a/assets/slides.html +++ b/assets/slides.html @@ -1266,9 +1266,6 @@

Polyglot programming for single-cell analysis

-
- -

Introduction

    @@ -1413,7 +1410,7 @@

    Rpy2

  1. rpy2.robjects, the high-level interface
    2. -
    +
    import rpy2
 import rpy2.robjects as robjects
 
@@ -1440,7 +1437,7 @@ 
    Rpy2
    
 
    
 
 
    Rpy2: basics
    
-
    
+
    
 
    str_vector = robjects.StrVector(['abc', 'def', 'ghi'])
 flt_vector = robjects.FloatVector([0.3, 0.8, 0.7])
 int_vector = robjects.IntVector([1, 2, 3])
@@ -1460,7 +1457,7 @@ 
    Rpy2: basics
    
 
    
 
 
    Rpy2: numpy
    
-
    
+
    
 
    import numpy as np
 
 from rpy2.robjects import numpy2ri
@@ -1472,18 +1469,18 @@ 
    Rpy2: numpy
    
     mtx = robjects.r.matrix(rd_m, nrow = 5)
     print(mtx)
    
 
    
-
    [[0.31332317 0.35364146 0.56282682 0.85862223]
- [0.62741044 0.572032   0.69183808 0.7092725 ]
- [0.3976838  0.34202251 0.23438556 0.59881822]
- [0.78234652 0.99630959 0.18262528 0.83434156]
- [0.54189244 0.31409299 0.85954986 0.70672631]]
    
+
    [[0.92902919 0.24572561 0.13860008 0.62978886]
+ [0.21979936 0.43720737 0.61998573 0.49151776]
+ [0.99598827 0.35626021 0.12943936 0.15135163]
+ [0.8411791  0.3295325  0.76558594 0.32489612]
+ [0.2671875  0.25684477 0.88505818 0.14963159]]
    
 
    
 
    
 
    
 
    
 
 
    Rpy2: pandas
    
-
    
+
    
 
    import pandas as pd
 
 from rpy2.robjects import pandas2ri
@@ -1506,7 +1503,7 @@ 
    Rpy2: pandas
    
 
    
 
 
    Rpy2: sparse matrices
    
-
    
+
    
 
    import scipy as sp
 
 from anndata2ri import scipy2ri
@@ -1519,11 +1516,11 @@ 
    Rpy2: sparse matrices
    
 
    
 
    5 x 4 sparse Matrix of class "dgCMatrix"
                                             
-[1,] 0.3133232 0.3536415 0.5628268 0.8586222
-[2,] 0.6274104 0.5720320 0.6918381 0.7092725
-[3,] 0.3976838 0.3420225 0.2343856 0.5988182
-[4,] 0.7823465 0.9963096 0.1826253 0.8343416
-[5,] 0.5418924 0.3140930 0.8595499 0.7067263
+[1,] 0.9290292 0.2457256 0.1386001 0.6297889
+[2,] 0.2197994 0.4372074 0.6199857 0.4915178
+[3,] 0.9959883 0.3562602 0.1294394 0.1513516
+[4,] 0.8411791 0.3295325 0.7655859 0.3248961
+[5,] 0.2671875 0.2568448 0.8850582 0.1496316
 
    
 
    
 
    
@@ -1641,9 +1638,6 @@ 
    Reticulate scanpy
    
 #     obsm: 'HTO_clr', 'X_pca', 'X_umap', 'protein_counts'
 #     varm: 'PCs'
 #     obsp: 'connectivities', 'distances'
    
-
    
-
    
-
 
    
 
    
 
    Disk-based interoperability
    
@@ -1955,16 +1949,18 @@ 
    Define tasks in Pixi
    
 
    Also possible to use containers
    
 
    docker pull berombau/polygloty-docker:latest
 docker run -it -v $(pwd)/usecase:/app/usecase -v $(pwd)/book:/app/book berombau/polygloty-docker:latest pixi run pipeline
    
-
    Another approach is to use multi-package containers to create custom combinations of packages. - Multi-Package BioContainers - Seqera Containers
    
+

Workflows

You can go a long way with a folder of notebooks or scripts and the right tools. But as your project grows more bespoke, it can be worth the effort to use a workflow framework like Viash, Nextflow or Snakemake to manage the pipeline for you.

See https://saeyslab.github.io/polygloty/book/workflow_frameworks/

-
- -
-

Takeaways

diff --git a/assets/slides.pdf b/assets/slides.pdf index 1019c90..6b0917f 100644 Binary files a/assets/slides.pdf and b/assets/slides.pdf differ diff --git a/slides/images/scverse2025.jpg b/slides/images/scverse2025.jpg new file mode 100644 index 0000000..69a0ec6 Binary files /dev/null and b/slides/images/scverse2025.jpg differ diff --git a/slides/slides.html b/slides/slides.html index ff44f3d..32621e5 100644 --- a/slides/slides.html +++ b/slides/slides.html @@ -1266,9 +1266,6 @@

Polyglot programming for single-cell analysis

-
- -

Introduction

    @@ -1413,7 +1410,7 @@

    Rpy2

  1. rpy2.robjects, the high-level interface
    2. -
    +
    import rpy2
 import rpy2.robjects as robjects
 
@@ -1440,7 +1437,7 @@ 
    Rpy2
    
 
    
 
 
    Rpy2: basics
    
-
    
+
    
 
    str_vector = robjects.StrVector(['abc', 'def', 'ghi'])
 flt_vector = robjects.FloatVector([0.3, 0.8, 0.7])
 int_vector = robjects.IntVector([1, 2, 3])
@@ -1460,7 +1457,7 @@ 
    Rpy2: basics
    
 
    
 
 
    Rpy2: numpy
    
-
    
+
    
 
    import numpy as np
 
 from rpy2.robjects import numpy2ri
@@ -1472,18 +1469,18 @@ 
    Rpy2: numpy
    
     mtx = robjects.r.matrix(rd_m, nrow = 5)
     print(mtx)
    
 
    
-
    [[0.31332317 0.35364146 0.56282682 0.85862223]
- [0.62741044 0.572032   0.69183808 0.7092725 ]
- [0.3976838  0.34202251 0.23438556 0.59881822]
- [0.78234652 0.99630959 0.18262528 0.83434156]
- [0.54189244 0.31409299 0.85954986 0.70672631]]
    
+
    [[0.92902919 0.24572561 0.13860008 0.62978886]
+ [0.21979936 0.43720737 0.61998573 0.49151776]
+ [0.99598827 0.35626021 0.12943936 0.15135163]
+ [0.8411791  0.3295325  0.76558594 0.32489612]
+ [0.2671875  0.25684477 0.88505818 0.14963159]]
    
 
    
 
    
 
    
 
    
 
 
    Rpy2: pandas
    
-
    
+
    
 
    import pandas as pd
 
 from rpy2.robjects import pandas2ri
@@ -1506,7 +1503,7 @@ 
    Rpy2: pandas
    
 
    
 
 
    Rpy2: sparse matrices
    
-
    
+
    
 
    import scipy as sp
 
 from anndata2ri import scipy2ri
@@ -1519,11 +1516,11 @@ 
    Rpy2: sparse matrices
    
 
    
 
    5 x 4 sparse Matrix of class "dgCMatrix"
                                             
-[1,] 0.3133232 0.3536415 0.5628268 0.8586222
-[2,] 0.6274104 0.5720320 0.6918381 0.7092725
-[3,] 0.3976838 0.3420225 0.2343856 0.5988182
-[4,] 0.7823465 0.9963096 0.1826253 0.8343416
-[5,] 0.5418924 0.3140930 0.8595499 0.7067263
+[1,] 0.9290292 0.2457256 0.1386001 0.6297889
+[2,] 0.2197994 0.4372074 0.6199857 0.4915178
+[3,] 0.9959883 0.3562602 0.1294394 0.1513516
+[4,] 0.8411791 0.3295325 0.7655859 0.3248961
+[5,] 0.2671875 0.2568448 0.8850582 0.1496316
 
    
 
    
 
    
@@ -1641,9 +1638,6 @@ 
    Reticulate scanpy
    
 #     obsm: 'HTO_clr', 'X_pca', 'X_umap', 'protein_counts'
 #     varm: 'PCs'
 #     obsp: 'connectivities', 'distances'
    
-
    
-
    
-
 
    
 
    
 
    Disk-based interoperability
    
@@ -1955,16 +1949,18 @@ 
    Define tasks in Pixi
    
 
    Also possible to use containers
    
 
    docker pull berombau/polygloty-docker:latest
 docker run -it -v $(pwd)/usecase:/app/usecase -v $(pwd)/book:/app/book berombau/polygloty-docker:latest pixi run pipeline
    
-
    Another approach is to use multi-package containers to create custom combinations of packages. - Multi-Package BioContainers - Seqera Containers
    
+

Workflows

You can go a long way with a folder of notebooks or scripts and the right tools. But as your project grows more bespoke, it can be worth the effort to use a workflow framework like Viash, Nextflow or Snakemake to manage the pipeline for you.

See https://saeyslab.github.io/polygloty/book/workflow_frameworks/

-
- -
-

Takeaways

diff --git a/slides/slides.pdf b/slides/slides.pdf index 1019c90..6b0917f 100644 Binary files a/slides/slides.pdf and b/slides/slides.pdf differ diff --git a/slides/slides.qmd b/slides/slides.qmd index f63b34d..31aec17 100644 --- a/slides/slides.qmd +++ b/slides/slides.qmd @@ -24,7 +24,6 @@ execute: ![](images/scverse2025.jpg) ---- # Introduction @@ -375,8 +374,6 @@ adata # obsp: 'connectivities', 'distances' ``` ---- - # Disk-based interoperability Disk-based interoperability is a strategy for achieving interoperability between tools written in different programming languages by **storing intermediate results in standardized, language-agnostic file formats**. @@ -473,9 +470,9 @@ docker pull berombau/polygloty-docker:latest docker run -it -v $(pwd)/usecase:/app/usecase -v $(pwd)/book:/app/book berombau/polygloty-docker:latest pixi run pipeline ``` -Another approach is to use multi-package containers to create custom combinations of packages. -- [Multi-Package BioContainers](https://midnighter.github.io/mulled/) -- [Seqera Containers](https://seqera.io/containers/) +- Another approach is to use multi-package containers to create custom combinations of packages. + - [Multi-Package BioContainers](https://midnighter.github.io/mulled/) + - [Seqera Containers](https://seqera.io/containers/) # Workflows @@ -484,4 +481,3 @@ You can go a long way with a folder of notebooks or scripts and the right tools. See https://saeyslab.github.io/polygloty/book/workflow_frameworks/ -# Takeaways