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add static version of notebooks
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docs/source/experiment_create.ipynb renamed to docs/notebooks/experiment_create.ipynb

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"# Generate a new auth_token in your profile and post it here\n",
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"auth_token = 'AseyaNLLhqv9jAm0joMkq2oqB0bw3GKxTclkT2NtG340RF6CfdM2UC3j8Fv4RpbQ'"
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"auth_token = 'R2skRbpBD3Rsf5dNHoQxDZevdEE74T5lCKMFyBhBwwPFH4ZfTrxDz7TZ0kbFLtEZ'"
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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": "3.9.7"
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"version": "3.9.9"
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}
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"nbformat": 4,

‎docs/notebooks/experiment_get.ipynb‎

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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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"# GET experiment"
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]
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},
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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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"## get an experiment from MaveDB via the API"
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]
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},
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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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"To begin, import the modeules below."
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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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"source": [
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"import attr, os\n",
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"from pprint import PrettyPrinter\n",
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"from mavetools.client.client import Client\n",
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"from mavetools.models.experiment import Experiment"
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]
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},
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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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"Pretty printer is used to format the output nicely. "
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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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"pp = PrettyPrinter(indent=2) # displayes results in readable format"
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]
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},
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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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"Here your base_url is set to localhost, http://127.0.0.1:8000/api/. This default funcionality is what you would want to use when working with a local instance of MaveDB (e.g., a development branch). If working with production mavedb you would set base url to https://www.mavedb.org/api/.\n",
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"\n",
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"In the cell below, comment out the base_url you will not be using."
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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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"source": [
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"base_url = 'http://127.0.0.1:8000/api/'\n",
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"#base_url = 'https://www.mavedb.org/api/'"
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]
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},
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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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"Set experiment_urn to match the experiment you want to get."
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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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"source": [
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"experiment_urn = 'urn:mavedb:00000001-a'"
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]
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},
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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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"Next, you will need an auth_token to make POST requests to MaveDB. If you have one, substitute it in the example provided below. If you need one, please follow these instructions:\n",
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"\n",
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" 1. go to https://www.mavedb.org\n",
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" 2. login using your ORCID ID\n",
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" 3. go to settings\n",
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" 4. generate new auth token\n",
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" 5. copy auth token and pase it in the auth_token field below"
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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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"source": [
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"# Generate a new auth_token in your profile and post it here\n",
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"auth_token = 'R2skRbpBD3Rsf5dNHoQxDZevdEE74T5lCKMFyBhBwwPFH4ZfTrxDz7TZ0kbFLtEZ'"
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]
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},
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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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"Here you instantiate the Client object. The Client object is the object by which the POST request is performed. The client object is instantiated with the value of base_url provided earlier, so make sure that is up-to-date. If base_url does not exist, base_url is defaulted to localhost, http://127.0.0.1:8000/api/."
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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": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"client = Client(base_url, auth_token=auth_token) if base_url else Client(auth_token=auth_token)"
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]
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},
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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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"GET the model instance by passing the model type (Experiment, in this instance) and the experiment_urn as arguments to the get_model_istance funtion that operates on the Client object. This will GET the model instance (resource) from the server via the approprate API endpoint."
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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": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"experiment = client.get_model_instance(Experiment, experiment_urn)"
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]
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},
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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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"Now, display the results!"
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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": 8,
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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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"{ 'abstract_text': 'Although we now routinely sequence human genomes, we can '\n",
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" 'confidently identify only a fraction of the sequence '\n",
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" 'variants that have a functional impact. Here, we developed '\n",
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" 'a deep mutational scanning framework that produces '\n",
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" 'exhaustive maps for human missense variants by combining '\n",
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" 'random codon mutagenesis and multiplexed functional '\n",
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" 'variation assays with computational imputation and '\n",
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" 'refinement. We applied this framework to four proteins '\n",
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" 'corresponding to six human genes: UBE2I (encoding SUMO E2 '\n",
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" 'conjugase), SUMO1 (small ubiquitin-like modifier), TPK1 '\n",
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" '(thiamin pyrophosphokinase), and CALM1/2/3 (three genes '\n",
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" 'encoding the protein calmodulin). The resulting maps '\n",
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" 'recapitulate known protein features and confidently '\n",
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" 'identify pathogenic variation. Assays potentially amenable '\n",
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" 'to deep mutational scanning are already available for 57% '\n",
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" 'of human disease genes, suggesting that DMS could '\n",
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" 'ultimately map functional variation for all human disease '\n",
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" 'genes.',\n",
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" 'approved': None,\n",
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" 'contributors': ['0000-0003-1628-9390'],\n",
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" 'created_by': '0000-0003-1628-9390',\n",
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" 'creation_date': '2018-06-26',\n",
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" 'doi_ids': [],\n",
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" 'experimentset': 'urn:mavedb:00000001',\n",
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" 'extra_metadata': {},\n",
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" 'keywords': [ {'text': 'E2'},\n",
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" {'text': 'sumoylation'},\n",
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" {'text': 'imputation'},\n",
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" {'text': 'complementation'}],\n",
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" 'last_child_value': None,\n",
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" 'method_text': 'A Deep Mutational Scan of UBE2I using functional '\n",
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" 'complementation in yeast was performed using two different '\n",
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" 'methods: DMS-BarSeq and DMS-TileSeq, both datasets were '\n",
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" 'combined and a machine-learning method was used to impute '\n",
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" 'the effects of missing variants and refine measurements of '\n",
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" 'lower confidence. See [**Weile *et al.* '\n",
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" '2017**](http://msb.embopress.org/content/13/12/957) for '\n",
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" 'details.',\n",
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" 'modification_date': '2019-08-08',\n",
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" 'modified_by': '0000-0003-1628-9390',\n",
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" 'private': None,\n",
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" 'publish_date': '2018-06-26',\n",
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" 'pubmed_ids': [ { 'dbname': 'PubMed',\n",
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" 'dbversion': None,\n",
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" 'identifier': '29269382',\n",
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" 'url': 'http://www.ncbi.nlm.nih.gov/pubmed/29269382'}],\n",
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" 'scoresets': [ 'urn:mavedb:00000001-a-2',\n",
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" 'urn:mavedb:00000001-a-3',\n",
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" 'urn:mavedb:00000001-a-4',\n",
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" 'urn:mavedb:00000001-a-1'],\n",
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" 'short_description': 'A Deep Mutational Scan of the human SUMO E2 conjugase '\n",
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" 'UBE2I using functional complementation in yeast.',\n",
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" 'sra_ids': [ { 'dbname': 'SRA',\n",
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" 'dbversion': None,\n",
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" 'identifier': 'SRP109101',\n",
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" 'url': 'http://www.ebi.ac.uk/ena/data/view/SRP109101'},\n",
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" { 'dbname': 'SRA',\n",
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" 'dbversion': None,\n",
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" 'identifier': 'SRP109119',\n",
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" 'url': 'http://www.ebi.ac.uk/ena/data/view/SRP109119'}],\n",
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" 'title': 'UBE2I yeast complementation',\n",
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" 'urn': 'urn:mavedb:00000001-a'}\n"
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]
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}
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],
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"source": [
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"pp.pprint(attr.asdict(experiment))"
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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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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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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": "3.9.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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