Picard AlignmentSummaryMetrics - PCT_CHIMERA Definition

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Introduction

In the realm of genomics and next-generation sequencing (NGS), accurate alignment of reads to a reference genome is crucial for downstream analysis. However, chimeric reads, which are formed by the fusion of two or more distinct DNA fragments, can lead to incorrect conclusions and misinterpretation of results. To address this issue, tools like Picard's AlignmentSummaryMetrics provide metrics to identify and quantify chimeric reads. In this article, we will delve into the definition of PCT_CHIMERA, a key metric in AlignmentSummaryMetrics, and explore the discrepancies between its definition in the metric definitions and the tool documentation.

PCT_CHIMERA Definition: A Closer Look

The PCT_CHIMERA metric is defined in the Picard metric definitions as:

The fraction of reads that map outside of a maximum insert size (usually 100kb) or that have the two ends mapping to different chromosomes.

This definition suggests that chimeric reads are identified based on two criteria:

  1. Insert size: Reads that map outside of a maximum insert size (usually 100kb) are considered chimeric.
  2. Chromosome mapping: Reads that have the two ends mapping to different chromosomes are also considered chimeric.

However, the tool documentation provides a different definition of chimeras:

Chimeras are identified if any of the following criteria are met:

  • the insert size is larger than MAX_INSERT_SIZE
  • the ends of a pair map to different contigs
  • the paired end orientation is different that the expected orientation
  • the read contains an SA tag (chimeric alignment)

The tool documentation includes two additional read types as chimeric, based on pair orientation and those with supplementary alignments. This raises questions about which definition is correct and how PCT_CHIMERA is calculated.

Discrepancies and Clarifications

Upon closer inspection, it appears that the tool documentation provides a more comprehensive definition of chimeras, including additional criteria not mentioned in the metric definitions. The inclusion of SA tags (chimeric alignment) and supplementary alignments as chimeric read types suggests that the tool documentation is more accurate in its definition.

However, the metric definitions provide a clear and concise definition of PCT_CHIMERA, which is essential for understanding the metric's purpose and calculation. It is possible that the metric definitions are a simplified version of the tool documentation's definition, focusing on the core criteria for identifying chimeric reads.

Conclusion

In conclusion, the definition of PCT_CHIMERA in AlignmentSummaryMetrics is more complex than initially thought. While the metric definitions provide a clear definition of the metric, the tool documentation offers a more comprehensive definition of chimeras, including additional criteria. To accurately calculate PCT_CHIMERA, it is essential to consider all the criteria mentioned in the tool documentation.

Recommendations

Based on our analysis, we recommend the following:

  1. Use the tool documentation's definition: When working with AlignmentSummaryMetrics, use the tool documentation's definition of chimeras to ensure accurate identification and quantification of chimeric reads.
  2. Consider all criteria**: When calculating PCT_CHIMERA, consider all the criteria mentioned in the tool documentation, including SA tags (chimeric alignment) and supplementary alignments.
  3. Verify results: Verify the results of PCT_CHIMERA calculation to ensure accuracy and consistency with the tool documentation's definition.

By following these recommendations, researchers and analysts can ensure accurate and reliable results when working with AlignmentSummaryMetrics and PCT_CHIMERA.

Additional Resources

For further information on Picard's AlignmentSummaryMetrics and PCT_CHIMERA, refer to the following resources:

Introduction

In our previous article, we explored the definition of PCT_CHIMERA, a key metric in AlignmentSummaryMetrics, and discussed the discrepancies between its definition in the metric definitions and the tool documentation. In this article, we will address some of the most frequently asked questions (FAQs) related to PCT_CHIMERA and provide clarification on its calculation and usage.

Q&A

Q: What is the purpose of PCT_CHIMERA in AlignmentSummaryMetrics?

A: PCT_CHIMERA is a metric that measures the fraction of reads that are chimeric, meaning they are formed by the fusion of two or more distinct DNA fragments. This metric is essential for identifying and quantifying chimeric reads, which can lead to incorrect conclusions and misinterpretation of results.

Q: How is PCT_CHIMERA calculated?

A: PCT_CHIMERA is calculated based on the criteria mentioned in the tool documentation, including:

  • The insert size is larger than MAX_INSERT_SIZE
  • The ends of a pair map to different contigs
  • The paired end orientation is different than the expected orientation
  • The read contains an SA tag (chimeric alignment)
  • Supplementary alignments

Q: What is the difference between PCT_CHIMERA and other chimeric read metrics?

A: PCT_CHIMERA is a specific metric that measures the fraction of chimeric reads, whereas other metrics, such as CHIMERA_RATE, may measure the rate of chimeric reads or the number of chimeric reads per unit of sequencing data. The choice of metric depends on the specific research question and analysis goals.

Q: How can I use PCT_CHIMERA in my analysis?

A: To use PCT_CHIMERA in your analysis, follow these steps:

  1. Run the CollectAlignmentSummaryMetrics tool to generate the AlignmentSummaryMetrics file.
  2. Use the PCT_CHIMERA metric to identify and quantify chimeric reads.
  3. Consider all the criteria mentioned in the tool documentation to ensure accurate calculation of PCT_CHIMERA.
  4. Verify the results of PCT_CHIMERA calculation to ensure accuracy and consistency with the tool documentation's definition.

Q: What are some common pitfalls to avoid when working with PCT_CHIMERA?

A: Some common pitfalls to avoid when working with PCT_CHIMERA include:

  • Failing to consider all the criteria mentioned in the tool documentation, leading to inaccurate calculation of PCT_CHIMERA.
  • Not verifying the results of PCT_CHIMERA calculation, leading to incorrect conclusions and misinterpretation of results.
  • Using PCT_CHIMERA as a standalone metric without considering other metrics and analysis results.

Q: Where can I find more information on PCT_CHIMERA and AlignmentSummaryMetrics?

A: For further information on PCT_CHIMERA and AlignmentSummaryMetrics, refer to the following resources:

By understanding the definition and calculation of PCT_CHIMERA, researchers and analysts can ensure accurate and reliable results when working with AlignmentSummaryMetrics and Picard tools.

Additional Resources

For further information on Picard's AlignmentSummaryMetrics and PCT_CHIMERA, refer to the following resources:

By understanding the definition and calculation of PCT_CHIMERA, researchers and analysts can ensure accurate and reliable results when working with AlignmentSummaryMetrics and Picard tools.