Seurat: convert seurat to anndata: anndata.object$write(filename) not working

[aopisco]

hey! I'm trying to write a Seurat object to anndata but it fails in the write part

adata <- Convert(sc, to = "anndata")

works no problem

adata <- Convert(sc, to = "anndata",filename = "~/Lung_facs_seurat.h5ad")
Error in py_call_impl(callable, dots$args, dots$keywords) : ValueError: name already used as a name or title

[satijalab]

Thanks! We're aware that the anndata convert is throwing errors in some cases, and are working to fix before the formal v3 release. Apologies for the delay in the mean time

[hejing3283]

I am trying to save seurat object into h5ad so that I can visualize it using cellxgene. Is there any progress regarding this issue?

[aopisco]

hi @hejing3283, lately I've been able to convert between Seurat and h5ad with a few tricks. I'd suggest for you to compute everything in Seurat such that your Seurat object as all the slots filled. Once you do that try using the Convert function. If it doesn't work message me and I'll be able to help -- and good choice on cellxgene, it is a great tool! :)

[hejing3283]

Hi @aopisco , thanks for the suggestion! are you using Seurat V3 or V2?

[aopisco]

@hejing3283 I'm using V2 - didn't try V3 yet

[hejing3283]

I am using V3. I found many conversion function didn't work in V3. so stay
with V2.

On Wed, May 8, 2019 at 12:18 PM aopisco [e-mail] wrote:

@hejing3283 https://github.com/hejing3283 I'm using V2 - didn't try V3
yet

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[mojaveazure]

Hi all,

We currently do not support direct Seurat → AnnData conversion. We do have a work around by allowing users to write out to a loom file with as.loom, then reading the loom file in Python with Scanpy/AnnData

[hejing3283]

Thanks!

On Fri, May 17, 2019 at 11:23 AM Paul Hoffman [e-mail]
wrote:

Hi all,

We currently do not support direct Seurat ↔ AnnData conversion. We do have
a work around by allowing users to write out to a loom file with as.loom,
then reading the loom file in Python with Scanpy/AnnData

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[alextamburino]

Hi Paul,

Is there a plan to support direct Seurat -> AnnData conversion soon? i.e. https://rdrr.io/github/satijalab/seurat/man/h5ad.html

I'm trying to convert for use with cellxgene without using Python.

Thanks,
Alex

[hejing3283]

Hi Alex,

I was able to do it by Seurat=>loom==>h5ad
H5ad is what cellxgene needed. This is working for the most updated version of Seurat v3.

Best,
Jing

On Jun 25, 2019, at 11:18, Alex Tamburino [e-mail] wrote:

Hi Paul,

Is there a plan to support direct Seurat -> AnnData conversion soon? i.e. https://rdrr.io/github/satijalab/seurat/man/h5ad.html

I'm trying to convert for use with cellxgene without using Python.

Thanks,
Alex

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[alextamburino]

Hi Jing,

Thanks for the info. Can you please elaborate?

Alex

[hejing3283]

Hi.

Here is what I did.

$ R

require(Seurat)

devtools::install_github(repo = 'hhoeflin/hdf5r') # Update hdf5r for
stability improvements

devtools::install_github(repo = 'mojaveazure/loomR', ref = 'develop’)

require(loomR)
sessionInfo()

[1] Seurat_3.0.1 loomR_0.2.1.9000 hdf5r_1.2.0

load(’SEURAT_OBJ.Rdata’)

Seurat.obj.ad = as.loom(seurat.obj, filename=’SEURAT_OBJ.loom’)

q()

python

$ conda activate YOUR_ENV

$ pip install -U loompy

$ pip install scanpy==1.4.3

$ python

import scanpy as sc

import loompy

print(loompy.__version__) ## 2.0.17

adata = sc.read_loom('SEURAT_OBJ.loom')

adata.write('SEURAT_OBJ.h5ad')

exit()

$ cellxgene prepare --layout umap SEURAT_OBJ.h5ad --output
SEURAT_OBJ_umap.h5ad ## if layout not computed

$ cellxgene launch --layout tsne SEURAT_OBJ_umap.h5ad --open

On Tue, Jun 25, 2019 at 1:15 PM Alex Tamburino [e-mail]
wrote:

Hi Jing,

Thanks for the info. Can you please elaborate?

Alex

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[alextamburino]

Thanks Jing!

On Thu, Jun 27, 2019 at 10:34 AM Jing He [e-mail] wrote:

Hi.

Here is what I did.

$ R

require(Seurat)

devtools::install_github(repo = 'hhoeflin/hdf5r') # Update hdf5r for
stability improvements

devtools::install_github(repo = 'mojaveazure/loomR', ref = 'develop’)

require(loomR)
sessionInfo()

[1] Seurat_3.0.1 loomR_0.2.1.9000 hdf5r_1.2.0

load(’SEURAT_OBJ.Rdata’)

Seurat.obj.ad = as.loom(seurat.obj, filename=’SEURAT_OBJ.loom’)

q()

python

$ conda activate YOUR_ENV

$ pip install -U loompy

$ pip install scanpy==1.4.3

$ python

import scanpy as sc

import loompy

print(loompy.__version__) ## 2.0.17

adata = sc.read_loom('SEURAT_OBJ.loom')

adata.write('SEURAT_OBJ.h5ad')

exit()

$ cellxgene prepare --layout umap SEURAT_OBJ.h5ad --output
SEURAT_OBJ_umap.h5ad ## if layout not computed

$ cellxgene launch --layout tsne SEURAT_OBJ_umap.h5ad --open

On Tue, Jun 25, 2019 at 1:15 PM Alex Tamburino [e-mail]
wrote:

Hi Jing,

Thanks for the info. Can you please elaborate?

Alex

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[hejing3283]

Np.

Best,
Jing

On Jun 27, 2019, at 12:26, Alex Tamburino [e-mail] wrote:

Thanks Jing!

On Thu, Jun 27, 2019 at 10:34 AM Jing He [e-mail] wrote:

Hi.

Here is what I did.

$ R

require(Seurat)

devtools::install_github(repo = 'hhoeflin/hdf5r') # Update hdf5r for
stability improvements

devtools::install_github(repo = 'mojaveazure/loomR', ref = 'develop’)

require(loomR)
sessionInfo()

[1] Seurat_3.0.1 loomR_0.2.1.9000 hdf5r_1.2.0

load(’SEURAT_OBJ.Rdata’)

Seurat.obj.ad = as.loom(seurat.obj, filename=’SEURAT_OBJ.loom’)

q()

python

$ conda activate YOUR_ENV

$ pip install -U loompy

$ pip install scanpy==1.4.3

$ python

import scanpy as sc

import loompy

print(loompy.__version__) ## 2.0.17

adata = sc.read_loom('SEURAT_OBJ.loom')

adata.write('SEURAT_OBJ.h5ad')

exit()

$ cellxgene prepare --layout umap SEURAT_OBJ.h5ad --output
SEURAT_OBJ_umap.h5ad ## if layout not computed

$ cellxgene launch --layout tsne SEURAT_OBJ_umap.h5ad --open

On Tue, Jun 25, 2019 at 1:15 PM Alex Tamburino [e-mail]
wrote:

Hi Jing,

Thanks for the info. Can you please elaborate?

Alex

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Jing

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[hk20013106]

Hi Jing,

I received an error when running adata = sc.read_loom('GM_OS.merge.loom')

ValueError Traceback (most recent call last)
in
1 #pwd
----> 2 adata = sc.read_loom('GM_OS.merge.loom')
3 #adata.write('SEURAT_OBJ.h5ad')

D:Anaconda3libsite-packagesanndatareadwriteread.py in read_loom(filename, sparse, cleanup, X_name, obs_names, var_names, dtype, **kwargs)
158
159 if X_name not in lc.layers.keys(): X_name = ''
--> 160 X = lc.layers[X_name].sparse().T.tocsr() if sparse else lc.layers[X_name][()].T
161
162 layers = OrderedDict()

D:Anaconda3libsite-packagesloompyloom_layer.py in sparse(self, rows, cols)
109 col: List[np.ndarray] = []
110 i = 0
--> 111 for (ix, selection, view) in self.ds.scan(items=cols, axis=1, layers=[self.name]):
112 if rows is not None:
113 vals = view.layers[self.name][rows, :]

D:Anaconda3libsite-packagesloompyloompy.py in scan(self, items, axis, layers, key, batch_size)
597 for key, layer in vals.items():
598 lm[key] = loompy.MemoryLoomLayer(key, layer)
--> 599 view = loompy.LoomView(lm, self.ra[ordering], self.ca[ix + selection], self.row_graphs[ordering], self.col_graphs[ix + selection], filename=self.filename, file_attrs=self.attrs)
600 yield (ix, ix + selection, view)
601 ix += cols_per_chunk

D:Anaconda3libsite-packagesloompygraph_manager.py in __getitem__(self, thing)
96 if type(thing) is slice or type(thing) is np.ndarray or type(thing) is int:
97 gm = GraphManager(None, axis=self.axis)
---> 98 for key, g in self.items():
99 # Slice the graph matrix properly without making it dense
100 (a, b, w) = (g.row, g.col, g.data)

D:Anaconda3libsite-packagesloompygraph_manager.py in items(self)
55 def items(self) -> Iterable[Tuple[str, sparse.coo_matrix]]:
56 for key in self.keys():
---> 57 yield (key, self[key])
58
59 def __len__(self) -> int:

D:Anaconda3libsite-packagesloompygraph_manager.py in __getitem__(self, thing)
116 raise AttributeError(f"'{type(self)}' object has no attribute {thing}")
117 else:
--> 118 return self.__getattr__(thing)
119
120 def __getattr__(self, name: str) -> sparse.coo_matrix:

D:Anaconda3libsite-packagesloompygraph_manager.py in __getattr__(self, name)
127 c = self.ds._file[a][name]["b"]
128 w = self.ds._file[a][name]["w"]
--> 129 g = sparse.coo_matrix((w, (r, c)), shape=(self.ds.shape[self.axis], self.ds.shape[self.axis]))
130 self.__dict__["storage"][name] = g
131 return g

D:Anaconda3libsite-packagesscipysparsecoo.py in __init__(self, arg1, shape, dtype, copy)
196 self.data = self.data.astype(dtype, copy=False)
197
--> 198 self._check()
199
200 def reshape(self, args, *kwargs):

D:Anaconda3libsite-packagesscipysparsecoo.py in _check(self)
285 raise ValueError('row index exceeds matrix dimensions')
286 if self.col.max() >= self.shape[1]:
--> 287 raise ValueError('column index exceeds matrix dimensions')
288 if self.row.min() < 0:
289 raise ValueError('negative row index found')

ValueError: column index exceeds matrix dimensions

Do you have any idea?
Thank you very much!

Kai

[carmensandoval]

Hi,

I'm also trying to convert my Seurat object to h5ad for use with cellxgene.

I'm following @hejing3283 's workflow

neocortex.loom <- as.loom(Neocortex, file="neocortex.loom")

Error in loomR::create(filename = filename, data = GetAssayData(object = x,  :
  unused arguments (feature.attrs = as.list(x = meta.feature), transpose = TRUE, 
calc.count = FALSE, max.size = max.size, verbose = verbose)

$ R
devtools::install_github(repo = 'mojaveazure/loomR') (*)
require(loomR) 

sessionInfo()
[1] Seurat_3.0.1 loomR_0.2.0

 load(’Neocortex.Rdata’) 

(*) Unfortunately, we cannot install the hdf5r package on our cluster - it is too outdated. So I can only install loomR 0.2.0 (not the 'develop' version, as that one calls hdf5r). However, I don't think this is the reason for the error.