The workflow graphs provide metrics that allow you to judge the success of the sequencing run for that sample. The following topics provide information about these charts.
Low Percentage Graph
What is it
The workflow graphs provide metrics that allow you to judge the success of the sequencing run for that sample. The following topics provide information about these charts.

When to use it
Use the Low Percentage Graph to judge sequencing metrics for a sample. This graph can also be used when troubleshooting unexpected results.
When not to use it
This graph is not a good predictor of yields or quality of final results.
How to use it
Metric | Description |
---|---|
Phasing 1 | The percentage of molecules in a cluster that fall behind the current cycle within Read 1. |
Phasing 2 | The percentage of molecules in a cluster that fall behind the current cycle within Read 2. |
PrePhasing 1 | The percentage of molecules in a cluster that run ahead of the current cycle within Read 1. |
PrePhasing 2 | The percentage of molecules in a cluster that run ahead of the current cycle within Read 2. |
Mismatch 1 | The average percentage of mismatches for Read 1 over all cycles. |
Mismatch 2 | The average percentage of mismatches for Read 2 over all cycles. |
High Percentage Graph
What is it
The High Percentage Graph represents run statistics that are generally near 100% in an ideal run. These graphs are metrics of the sequencing run or the analysis step.

When to use it
Use the High Percentage Graph to judge sequencing metrics for a sample. This graph can also be used when troubleshooting unexpected results.
When not to use it
Do not use the High Percentage Graph to look at tertiary analysis metrics.
How to use it
Metric | Description |
---|---|
|20/|1 1 | The ratio of intensities at cycle 20 to the intensities at cycle 1 for Read 1. |
|20/|1 2 | The ratio of intensities at cycle 20 to the intensities at cycle 1 for Read 2. |
Align 1 | The percentage of clusters that aligned to the reference in Read 1. |
Align 2 | The percentage of clusters that aligned to the reference in Read 2. |
PE Orienation | The percentage of paired-end alignments with the expected orientation. |
PE Resynthesis | The ratio of first cycle intensities for Read 1 to first cycle intensities for Read 2. |
PF | The percentage of clusters passing filters. |
Clusters Graph
What is it
The Clusters graph provides information about the number of clusters that are detected during sequencing, split out by the following groups:
- Total
- Passing filter
- Unaligned
- Unindexed
- Duplicates

When to use it
Use the Clusters Graph to judge clustering success and relative cluster density between lanes (for flow cells with multiple lanes), and as a snap shot of the overall run. Can assist with identifying overclustering issues.
When not to use it
Do not use the Clusters Graph to look at tertiary analysis metrics.
How to use it
A cluster represents a clonal spot on the flow cell that contains the amplified DNA strands to be sequenced.
X axis | Description |
---|---|
Raw | The total number of clusters detected in the run. |
PF | The total number of clusters passing filter in the run. |
Unaligned | The total number of clusters passing filter that did not align to the reference genome, if applicable. Clusters that are unindexed are not included in the unaligned count. |
Unindexed | The total number of clusters passing filter that were not associated with any index sequence in the run. |
Duplicate | The total number of clusters for a paired-end sequencing run that are considered to be PCR duplicates. PCR duplicates are defined as two clusters from a paired-end run where both clusters have the exact same alignment positions for each read. |
Mismatch Graph
What is it
The Mismatch Graph plots the mismatches between a sequence read and a reference genome after alignment.

When to use it
To judge the quality of the sequencing run. Poor sequencing runs usually lead to high numbers of mismatches.
When not to use it
- When you are using a reference genome that has many errors or low confidence stretches.
- When sample and reference differ too much.
- In de novo applications.
- In Methyl-Seq applications
How to use it
Mismatch refers to any mismatch between sequence read and a reference genome after alignment.
- Cycle: Plots the % mismatches for all clusters in a run versus cycle
Mismatches can be due to two main causes:
- Sequencing errors (non-specific, random)
- Differences between your sample and the reference genomes
Make sure to keep in mind these causes when interpreting the mismatch rates.
Trimmed Lengths
Y axis | X axis | Description |
---|---|---|
Clusters | Trimmed Lengths | Histogram of reads indicating length at trimming because they reached adapter. |