In this notebook, we upload cell type annotations assigned by our domain experts. These annotations were generated using markers and by interactive investigation of our .h5ad files.
As these are derived from our .h5ad files, we'll connect them to the HISE analysis chain by chaching those files and using hisepy.upload.upload_files().
import hisepy
from datetime import date
For T cells, this was done in multiple steps. First, we clustered all T cells, then we used these original clusters to identify several T cell subsets for iterative clustering.
Here, we'll combine these steps to build the link in our reproducibility chain.
in_files = [
'70651e60-282b-4ed0-96f6-414547297232', # Naive CD4 T cell .h5ad
'1ad9302d-6fd5-49b0-be4c-8a08492c7cb7', # MAIT CD8 T cell .h5ad
'6c1dff43-ddc5-437b-8e3d-dd5a32553b16', # CM CD8 T cell .h5ad
'b671c53a-2698-41c1-a886-9ab939306716', # EM CD8 T cell .h5ad
'35b11bcf-7a45-4714-b470-9f7627d6fbbd', # Treg cell .h5ad
'5ae29893-5a77-4081-86d1-523713a237e6', # Naive CD8 T cell .h5ad
'90a71622-5713-47f7-82e8-18e164ca9454', # Proliferating T cell .h5ad
'e5ec7efd-a210-4b98-9f45-f95ab5e6cc83', # gdT cell .h5ad
'd33ef147-59db-4fb6-950c-1dd8af242d4f', # ISG-high T cell .h5ad
'a04b6a89-81ff-43ca-b0f8-0b1939f407f1' # Other T cell .h5ad
]
hise_res = hisepy.reader.cache_files(in_files)
downloading fileID: 70651e60-282b-4ed0-96f6-414547297232 downloading fileID: 1ad9302d-6fd5-49b0-be4c-8a08492c7cb7 downloading fileID: 6c1dff43-ddc5-437b-8e3d-dd5a32553b16 downloading fileID: b671c53a-2698-41c1-a886-9ab939306716 downloading fileID: 35b11bcf-7a45-4714-b470-9f7627d6fbbd downloading fileID: 5ae29893-5a77-4081-86d1-523713a237e6 downloading fileID: 90a71622-5713-47f7-82e8-18e164ca9454 downloading fileID: e5ec7efd-a210-4b98-9f45-f95ab5e6cc83 downloading fileID: d33ef147-59db-4fb6-950c-1dd8af242d4f downloading fileID: a04b6a89-81ff-43ca-b0f8-0b1939f407f1 Files have been successfully downloaded!
out_files = [
'annotations/pbmc_ref_t-cd4-naive_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-mait_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-cd8-cm_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-cd8-em_annotations_2024-03-05.csv',
'annotations/pbmc_ref_treg_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-cd8-naive_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-proliferating_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-gd_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-isg-high_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-other_annotations_2024-03-05.csv'
]
study_space_uuid = '64097865-486d-43b3-8f94-74994e0a72e0'
title = 'T annotations {d}'.format(d = date.today())
hisepy.upload.upload_files(
files = out_files,
study_space_id = study_space_uuid,
title = title,
input_file_ids = in_files
)
annotations/pbmc_ref_t-cd4-naive_annotations_2024-03-05.csv annotations/pbmc_ref_t-mait_annotations_2024-03-05.csv annotations/pbmc_ref_t-cd8-cm_annotations_2024-03-05.csv annotations/pbmc_ref_t-cd8-em_annotations_2024-03-05.csv annotations/pbmc_ref_treg_annotations_2024-03-05.csv annotations/pbmc_ref_t-cd8-naive_annotations_2024-03-05.csv annotations/pbmc_ref_t-proliferating_annotations_2024-03-05.csv annotations/pbmc_ref_t-gd_annotations_2024-03-05.csv annotations/pbmc_ref_t-isg-high_annotations_2024-03-05.csv annotations/pbmc_ref_t-other_annotations_2024-03-05.csv you are trying to upload file_ids... ['annotations/pbmc_ref_t-cd4-naive_annotations_2024-03-05.csv', 'annotations/pbmc_ref_t-mait_annotations_2024-03-05.csv', 'annotations/pbmc_ref_t-cd8-cm_annotations_2024-03-05.csv', 'annotations/pbmc_ref_t-cd8-em_annotations_2024-03-05.csv', 'annotations/pbmc_ref_treg_annotations_2024-03-05.csv', 'annotations/pbmc_ref_t-cd8-naive_annotations_2024-03-05.csv', 'annotations/pbmc_ref_t-proliferating_annotations_2024-03-05.csv', 'annotations/pbmc_ref_t-gd_annotations_2024-03-05.csv', 'annotations/pbmc_ref_t-isg-high_annotations_2024-03-05.csv', 'annotations/pbmc_ref_t-other_annotations_2024-03-05.csv']. Do you truly want to proceed?
{'trace_id': 'fa2c1502-c7d5-42f5-894f-a5b23b1d6756',
'files': ['annotations/pbmc_ref_t-cd4-naive_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-mait_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-cd8-cm_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-cd8-em_annotations_2024-03-05.csv',
'annotations/pbmc_ref_treg_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-cd8-naive_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-proliferating_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-gd_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-isg-high_annotations_2024-03-05.csv',
'annotations/pbmc_ref_t-other_annotations_2024-03-05.csv']}
import session_info
session_info.show()
----- hisepy 0.3.0 session_info 1.0.0 -----
PIL 10.0.1 anyio NA arrow 1.3.0 asttokens NA attr 23.2.0 attrs 23.2.0 babel 2.14.0 beatrix_jupyterlab NA brotli NA cachetools 5.3.1 certifi 2024.02.02 cffi 1.16.0 charset_normalizer 3.3.2 cloudpickle 2.2.1 colorama 0.4.6 comm 0.1.4 cryptography 41.0.7 cycler 0.10.0 cython_runtime NA dateutil 2.8.2 db_dtypes 1.1.1 debugpy 1.8.0 decorator 5.1.1 defusedxml 0.7.1 deprecated 1.2.14 exceptiongroup 1.2.0 executing 2.0.1 fastjsonschema NA fqdn NA google NA greenlet 2.0.2 grpc 1.58.0 grpc_status NA h5py 3.10.0 idna 3.6 importlib_metadata NA ipykernel 6.28.0 ipython_genutils 0.2.0 ipywidgets 8.1.1 isoduration NA jedi 0.19.1 jinja2 3.1.2 json5 NA jsonpointer 2.4 jsonschema 4.20.0 jsonschema_specifications NA jupyter_events 0.9.0 jupyter_server 2.12.1 jupyterlab_server 2.25.2 jwt 2.8.0 kiwisolver 1.4.5 markupsafe 2.1.3 matplotlib 3.8.0 matplotlib_inline 0.1.6 mpl_toolkits NA nbformat 5.9.2 numpy 1.24.0 opentelemetry NA overrides NA packaging 23.2 pandas 2.1.4 parso 0.8.3 pexpect 4.8.0 pickleshare 0.7.5 pkg_resources NA platformdirs 4.1.0 plotly 5.18.0 prettytable 3.9.0 prometheus_client NA prompt_toolkit 3.0.42 proto NA psutil NA ptyprocess 0.7.0 pure_eval 0.2.2 pyarrow 13.0.0 pydev_ipython NA pydevconsole NA pydevd 2.9.5 pydevd_file_utils NA pydevd_plugins NA pydevd_tracing NA pygments 2.17.2 pyparsing 3.1.1 pyreadr 0.5.0 pythonjsonlogger NA pytz 2023.3.post1 referencing NA requests 2.31.0 rfc3339_validator 0.1.4 rfc3986_validator 0.1.1 rpds NA send2trash NA shapely 1.8.5.post1 six 1.16.0 sniffio 1.3.0 socks 1.7.1 sql NA sqlalchemy 2.0.21 sqlparse 0.4.4 stack_data 0.6.2 termcolor NA tornado 6.3.3 tqdm 4.66.1 traitlets 5.9.0 typing_extensions NA uri_template NA urllib3 1.26.18 wcwidth 0.2.12 webcolors 1.13 websocket 1.7.0 wrapt 1.15.0 xarray 2023.12.0 yaml 6.0.1 zipp NA zmq 25.1.2 zoneinfo NA
----- IPython 8.19.0 jupyter_client 8.6.0 jupyter_core 5.6.1 jupyterlab 4.1.2 notebook 6.5.4 ----- Python 3.10.13 | packaged by conda-forge | (main, Dec 23 2023, 15:36:39) [GCC 12.3.0] Linux-5.15.0-1052-gcp-x86_64-with-glibc2.31 ----- Session information updated at 2024-03-05 19:01