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Lernen Challenge: Summarize Gene Counts | Gene Expression Analysis and Reproducible Pipelines
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Python for Bioinformatics

bookChallenge: Summarize Gene Counts

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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.

Lösung

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.

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bookChallenge: Summarize Gene Counts

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Aufgabe

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.

Lösung

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.

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Abschnitt 3. Kapitel 2
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