Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Lära Challenge: Summarize Gene Counts | Gene Expression Analysis and Reproducible Pipelines
Practice
Projects
Quizzes & Challenges
Quizzes
Challenges
/
Python for Bioinformatics

bookChallenge: Summarize Gene Counts

Uppgift

Swipe to start coding

Write a Python function that summarizes gene count data from an RNA-seq experiment.

  • Calculate the total counts per gene by summing across all samples for each gene.
  • Calculate the total counts per sample by summing across all genes for each sample.
  • Compute the mean and median of the total counts per gene.
  • Compute the mean and median of the total counts per sample.
  • Return a dictionary with keys: "total_counts_per_gene", "total_counts_per_sample", "mean_gene_total", "median_gene_total", "mean_sample_total", and "median_sample_total", containing the corresponding results.

Lösning

Note
Note

The pandas library provides powerful methods to quickly summarize and analyze tabular data, such as gene count tables. Here is how the sum, mean, and median methods work, especially when using the axis parameter:

  • sum: Calculates the sum of values along a specified axis. Use axis=1 to sum across columns (totals for each row/gene) and axis=0 to sum across rows (totals for each column/sample);
  • mean: Computes the average value along a given axis. Use axis=1 for the mean across samples for each gene, or axis=0 for the mean across genes for each sample;
  • median: Finds the median value along a specified axis. Use axis=1 for the median across samples for each gene, or axis=0 for the median across genes for each sample.

For example, counts_df.sum(axis=1) returns the total counts for each gene by summing values across all samples. Setting axis=0 instead returns totals for each sample by summing across all genes. The same logic applies for mean and median. This flexibility allows you to easily calculate summary statistics for either genes or samples in your dataset.

Var allt tydligt?

Hur kan vi förbättra det?

Tack för dina kommentarer!

Avsnitt 3. Kapitel 2
single

single

Fråga AI

expand

Fråga AI

ChatGPT

Fråga vad du vill eller prova någon av de föreslagna frågorna för att starta vårt samtal

Suggested prompts:

Can you explain this in simpler terms?

What are the main benefits or drawbacks?

Can you give me a real-world example?

close

bookChallenge: Summarize Gene Counts

Svep för att visa menyn

Uppgift

Swipe to start coding

Write a Python function that summarizes gene count data from an RNA-seq experiment.

  • Calculate the total counts per gene by summing across all samples for each gene.
  • Calculate the total counts per sample by summing across all genes for each sample.
  • Compute the mean and median of the total counts per gene.
  • Compute the mean and median of the total counts per sample.
  • Return a dictionary with keys: "total_counts_per_gene", "total_counts_per_sample", "mean_gene_total", "median_gene_total", "mean_sample_total", and "median_sample_total", containing the corresponding results.

Lösning

Note
Note

The pandas library provides powerful methods to quickly summarize and analyze tabular data, such as gene count tables. Here is how the sum, mean, and median methods work, especially when using the axis parameter:

  • sum: Calculates the sum of values along a specified axis. Use axis=1 to sum across columns (totals for each row/gene) and axis=0 to sum across rows (totals for each column/sample);
  • mean: Computes the average value along a given axis. Use axis=1 for the mean across samples for each gene, or axis=0 for the mean across genes for each sample;
  • median: Finds the median value along a specified axis. Use axis=1 for the median across samples for each gene, or axis=0 for the median across genes for each sample.

For example, counts_df.sum(axis=1) returns the total counts for each gene by summing values across all samples. Setting axis=0 instead returns totals for each sample by summing across all genes. The same logic applies for mean and median. This flexibility allows you to easily calculate summary statistics for either genes or samples in your dataset.

Switch to desktopByt till skrivbordet för praktisk övningFortsätt där du är med ett av alternativen nedan
Var allt tydligt?

Hur kan vi förbättra det?

Tack för dina kommentarer!

Avsnitt 3. Kapitel 2
single

single

some-alt