Samples
Fragment length distribution
Plot help: Fragment length distribution
This plot shows the fragment length distribution of each experiment. The canonical ATAC-seq fragment length distribution has a sharp peak at short (50-100bp) fragment lengths, and broader peaks at fragment lengths that would span one, two or three nucleosomes.
Switching the y axis scale to exponential can reveal nucleosomal periodicity at higher fragment lengths.
Mouse over lines to see experiment details.
Double click or use the mouse wheel or trackpad scroll to zoom. Click and drag to pan.
Mouse over items in the sample list at the top of the page to highlight samples. Click them to toggle sample visibility.
The dashed red line is the reference fragment length distribution. You can toggle it on and off.
You can smooth the lines to make it easier to compare experiments, or make the plot more responsive if you have a lot of data. By default, smoothing is set to 10. For the most accurate plot, choose a smoothing value of one.
Distance from reference FLD
Plot help: distance from reference FLD
This plot shows how much the fragment length distribution of each experiment differs from the reference distribution defined for this instance of the ataqv results viewer. Generally, negative values indicate less transposition activity relative to the reference, while positive values indicate more. As you hover over libraries in this plot, watch the fragment length distribution plot (to the left or above, depending on your screen). Libraries on the right side of the reference should have clearer peaks than those on the left. It should be even more apparent if you set the fragment length distribution plot's y axis scale to exponential.
Mouse over dots to see experiment details.
Double click or use the mouse wheel or trackpad scroll to zoom. Click and drag to pan.
Mouse over items in the sample list at the top of the page to highlight samples. Click them to toggle sample visibility.
You can change the data source of the y axis with the Y AXIS select box below.
You can smooth the lines to make it easier to compare experiments, or make the plot more responsive if you have a lot of data.
TSS enrichment
Plot help: TSS enrichment
This plot shows mean enrichment of transposition events around transcription start sites.
Mouse over lines to see experiment details.
Double click or use the mouse wheel or trackpad scroll to zoom. Click and drag to pan.
Mouse over items in the sample list at the top of the page to highlight samples. Click them to toggle sample visibility.
Cumulative fraction of HQAA in peaks
Plot help: Cumulative fraction of HQAA in peaks
This plot shows each experiment's fraction of high-quality autosomal alignments that mapped within peaks.
Mouse over lines to see experiment details.
Double click or use the mouse wheel or trackpad scroll to zoom. Click and drag to pan.
Mouse over items in the sample list at the top of the page to highlight samples. Click them to toggle sample visibility.
The dashed red line represents the cumulative fraction of HQAA in the reference peak metrics defined when this viewer was created. You can toggle it on and off.
Cumulative fraction of peak territory
Plot help: Cumulative fraction of peak territory
This plot shows each experiment's cumulative fraction of peak territory.
Mouse over lines to see experiment details.
Double click or use the mouse wheel or trackpad scroll to zoom. Click and drag to pan.
Mouse over items in the sample list at the top of the page to highlight samples. Click them to toggle sample visibility.
The dashed red line represents the cumulative fraction of peak territory in the reference peak metrics defined when this viewer was created. You can toggle it on and off.
Mapping quality distribution
Plot help: Mapping quality distribution
This plot shows each experiment's mapping quality distribution.
Mouse over lines to see experiment details.
Double click or use the mouse wheel or trackpad scroll to zoom. Click and drag to pan.
Mouse over items in the sample list at the top of the page to highlight samples. Click them to toggle sample visibility.
Quality Indicators
Name | Sample | Library | High quality autosomal alignments (%) | Short-to-mononucleosomal ratio | Fragment length distribution distance from reference | TSS enrichment |
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Read Mapping Metrics
Name | Sample | Library | Total reads | Properly paired and mapped (%) | Secondary (%) | Supplementary (%) | Duplicate (%) | Mean mapping quality | Median mapping quality |
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Unmapped Read Metrics
Name | Sample | Library | Unmapped (%) | Unmapped mate (%) | QC fail (%) | Unpaired (%) | Zero mapping quality (%) |
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Aberrant Mapping Metrics
Name | Sample | Library | Of all reads, the percentage that paired and mapped but: | ||||||
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RF | FF | RR | on different chromosomes | too far from mate | just not properly |
Reference Mapping Metrics
Name | Sample | Library | Autosomal | Mitochondrial | ||
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% of all reads | Duplicates (% of autosomal alignments) | % of all reads | Duplicates (% of mitochondrial alignments) |
Peak Metrics
Name | Sample | Library | Total peaks | High quality autosomal alignments overlapping peaks (%) |
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Name | Sample | Library | Library description | Experiment description | ataqv metrics |
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Using the Plots tab
Each plot has specific help, but generally you can:
- Double click or use the mouse wheel or trackpad scrolling to zoom.
- Drag to pan.
- Hover over plot dots or lines to highlight them and see experiment details.
- Hover over samples to highlight samples in the plot.
- Click samples to toggle sample visibility in the plot.
Using the Tables tab
Hover over table headings to see descriptions of the metrics.
Filter the table by entering text in the Search box. Clear that box to restore the full table.
Most table headings can be clicked to sort the table.
Using the Experiments tab
If a URL was specified when running ataqv, the "Experiment description" column will contain links to more information on the experiments.
The original ataqv metrics files used to produce this viewer can be downloaded via the links in the last column. They're plain JSON files that you can use to produce your own plots with R or Pandas, or analyze further with your own programs.
You can search the experiment list by entering text in the Search box.