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Add pseudotemporal registration script (#340)
Signed-off-by: Lukas Heumos <lukas.heumos@posteo.net>
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environment.yml

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@@ -3,7 +3,9 @@ channels:
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- defaults
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- conda-forge
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dependencies:
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- conda-forge::python=3.11.8
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- conda-forge::jupyter-book==1.0.0
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- conda-forge::jupytext==1.16.1
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- conda-forge::beautifulsoup4==4.12.3
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- conda-forge::python=3.13
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- conda-forge::jupyter-book==1.0.3
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- conda-forge::jupytext==1.16.7
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- conda-forge::beautifulsoup4==4.13.3
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- pip:
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- lamindb[bionty,jupyter]
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Pseudotemporal dataset"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[92m→\u001b[0m connected lamindb: theislab/sc-best-practices\n"
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]
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}
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],
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"source": [
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"import lamindb as ln\n",
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"import scanpy as sc"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"assert ln.setup.settings.instance.slug == \"theislab/sc-best-practices\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[92m→\u001b[0m loaded Transform('6QcwslTJCWhW0001'), re-started Run('gunbofig...') at 2025-02-19 09:12:59 UTC\n",
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"\u001b[92m→\u001b[0m notebook imports: lamindb==1.1.0 scanpy==1.11.0\n"
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]
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}
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],
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"source": [
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"ln.track()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"AnnData object with n_obs × n_vars = 5780 × 27876\n",
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" obs: 'clusters', 'palantir_pseudotime', 'palantir_diff_potential'\n",
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" var: 'palantir'\n",
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" uns: 'clusters_colors', 'palantir_branch_probs_cell_types'\n",
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" obsm: 'MAGIC_imputed_data', 'X_tsne', 'palantir_branch_probs'\n",
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" layers: 'spliced', 'unspliced'"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"adata = sc.read(\n",
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" filename=\"bonemarrow.h5ad\",\n",
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" backup_url=\"https://figshare.com/ndownloader/files/35826944\",\n",
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")\n",
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"adata"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[92m→\u001b[0m found artifact with same hash: Artifact(uid='buvlHZTfCKo60akB0000', is_latest=True, key='trajectory/pseudotemporal.h5ad', description='pseudotemporal dataset', suffix='.h5ad', otype='AnnData', size=388391976, hash='FdzXtifrBdukftwBX2_m5M', space_id=1, storage_id=1, run_id=2, created_by_id=2, created_at=2025-02-19 08:38:20 UTC); to track this artifact as an input, use: ln.Artifact.get()\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"Artifact(uid='buvlHZTfCKo60akB0000', is_latest=True, key='trajectory/pseudotemporal.h5ad', description='pseudotemporal dataset', suffix='.h5ad', otype='AnnData', size=388391976, hash='FdzXtifrBdukftwBX2_m5M', space_id=1, storage_id=1, run_id=2, created_by_id=2, created_at=2025-02-19 08:38:20 UTC)"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"af = ln.Artifact(\n",
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" \"bonemarrow.h5ad\",\n",
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" key=\"trajectory/pseudotemporal.h5ad\",\n",
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" description=\"pseudotemporal dataset\",\n",
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").save()\n",
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"af"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"ln.finish()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "bp-pseudotime",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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