# HG changeset patch # User iuc # Date 1710430649 0 # Node ID 7b9fafe32c867a5b3b8f707ab3a7260db84ea3c6 # Parent 94c19fb1281c33107fcd4b8533069b099b92baf3 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit 3974c0ff86bb1d6633281f29dfb4c605a74e1e6e diff -r 94c19fb1281c -r 7b9fafe32c86 macros.xml --- a/macros.xml Fri Nov 17 09:16:03 2023 +0000 +++ b/macros.xml Thu Mar 14 15:37:29 2024 +0000 @@ -1,6 +1,6 @@ 1.9.6 - 1 + 2 22.05 @@ -11,6 +11,7 @@ pandas matplotlib seaborn + magic-impute diff -r 94c19fb1281c -r 7b9fafe32c86 normalize.xml --- a/normalize.xml Fri Nov 17 09:16:03 2023 +0000 +++ b/normalize.xml Thu Mar 14 15:37:29 2024 +0000 @@ -1,5 +1,5 @@ - with scanpy + and impute with scanpy macros.xml @@ -65,6 +65,29 @@ plot=False, copy=False) +#else if $method.method == "external.pp.magic" +sc.external.pp.magic( + adata=adata, + name_list='$method.name_list', + knn=$method.knn, + #if str($method.decay) != '' + decay=$method.decay, + #end if + #if str($method.knn_max) != '' + knn_max=$method.knn_max, + #end if + #if $method.t == -1 + t='auto', + #else + t=$method.t, + #end if + #if str($method.n_pca) != '' + n_pca=$method.n_pca, + #end if + solver='$method.solver', + knn_dist='$method.knn_dist', + random_state=$method.random_state, + copy=False) #end if @CMD_anndata_write_outputs@ @@ -79,6 +102,7 @@ + @@ -119,6 +143,29 @@ + + + + + + + + + + + + + + + + + + + @@ -217,6 +264,53 @@ + + + + + + + + + +
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`__ + +Markov Affinity-based Graph Imputation of Cells (MAGIC) as of Van Dijk D et al. (2018) (`external.pp.magic`) +============================================================================================================ + +MAGIC is an algorithm for denoising and transcript recover of single cells applied to single-cell sequencing data. MAGIC builds a graph from the data and uses diffusion to smooth out noise and recover the data manifold. + +The algorithm implemented here has changed primarily in two ways compared to the algorithm described in Van Dijk D et al. (2018). + +- Firstly, we use the adaptive kernel described in Moon et al, (2019) for improved stability. +- Secondly, data diffusion is applied in the PCA space, rather than the data space, for speed and memory improvements. + +More details on the `scanpy documentation +`__ + ]]>
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