- Course overview
- Search within this course
- Overview of key IMPC concepts and tools
- Introduction to the Solr API: accessing IMPC data programmatically
- What is Apache Solr?
- Important definitions: query, field, core, document, parameter
- Quiz 2: get yourself familiar with Solr terminology
- What is the difference between an IMPC parameter and a Solr parameter?
- Using simple Solr syntax in your browser
- Output of the simplest request in your browser
- A Python module to access IMPC data: installation and available functions
- Quiz 3: explain Solr request
- Solr query syntax: simplified explanation
- How to use the solr_request function from the impc-api python package
- How to perform a query: q parameter
- Exercise 1: getting familiar with the core
- How to request a limited number of documents: rows parameter
- Exercise 2: requesting three documents
- How to get specific fields: fl parameter
- Exercise 3: selecting specific fields
- Quiz 4: basic Solr parameters
- Filtering data in Solr: narrowing down your results
- How to query a specific field: filter by value
- Exercise 4: filtering by a single field
- How to filter numbers: range search
- Exercise 5: changing the p-value threshold
- How to combine multiple filters: Boolean operators
- Exercise 6: applying multiple filters
- How to exclude data: NOT operator
- Why parentheses are important: combine multiple Boolean operators
- Quiz 5: Boolean operators
- How to handle with null values: exclude empty fields
- Exercise 7: explore null values
- Downloading data: getting large results efficiently
- How to download large dataset effectively: pagination
- How to download the data: batch_solr_request function
- What formats are available for downloading: wt parameter
- Exercise 8: download the data
- What is the difference: JSON vs CSV
- What you need to keep in mind: query responsibly
- Quiz 6: request only necessary data
- Understanding IMPC data: resources and assistance
- Your feedback
Exercise 10: iterate over models
In this exercise, you have a list of genes. Run the script below and observe the result.
# Write genes to the Python list.
genes = ['Prkdc', 'Xrcc5', 'Xrcc4', 'Wrn']
# Iterate over list of genes.
df = batch_solr_request(
core='genotype-phenotype',
params={
'q':'*:*',
'fl': 'marker_symbol,mp_term_name,p_value',
'field_list': genes,
'field_type': 'marker_symbol'
},
download = False
)
display(df)
Go to exercise 10 in the Google Colab. Once you’ve finished Exercise 10 in the Google Colab, return here to continue the tutorial.
Show the correct answer
The function will generate a dataset that includes the genes from the list.
After completing this exercise, continue to the final section where you will learn more about the data available from the IMPC and how to find documentation.