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HQAA fragment length distribution (FLD)

Plot help: HQAA fragment length distribution (FLD)

This plot shows the high quality autosomal alignment (HQAA) fragment length distribution (FLD) of each experiment. The canonical ATAC-seq FLD 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 any line to see its experiment ID.

Click any line to see experiment details.

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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 any dot to see its experiment ID.

Click any dot 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.

TSS enrichment

Plot help: TSS enrichment

This plot shows mean enrichment of transposition events around transcription start sites, calculated per the ENCODE ATAC-seq data standards.

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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.

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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 any line to see its experiment ID.

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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 any line to see its experiment ID.

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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 HQAA (%) SMR FLDD TSS enrichment Duplicate fraction in peaks Duplicate fraction outside of peaks Peak duplicate ratio

Read Mapping Metrics

Name Sample Library Total reads Properly paired and mapped (%) Secondary (%) Supplementary (%) Duplicate (%) Mean mapping quality Median mapping quality

Unmapped Read Metrics

Name Sample Library Unmapped (%) Unmapped mate (%) QC fail (%) Unpaired (%) Zero mapping quality (%)

Aberrant Mapping Metrics

Name Sample Library Of all reads, the percentage that paired and mapped but:
Of all reads, the percentage that paired and mapped but RF Of all reads, the percentage that paired and mapped but FF Of all reads, the percentage that paired and mapped but RR Of all reads, the percentage that paired and mapped but on different chromosomes Of all reads, the percentage that paired and mapped but too far from mate Of all reads, the percentage that paired and mapped but just not properly

Reference Mapping Metrics

Name Sample Library Autosomal Mitochondrial
Autosomal, % of all reads Autosomal, Duplicates (% of autosomal alignments) Mitochondrial, % of all reads Mitochondrial, Duplicates (% of mitochondrial alignments)

Peak Metrics

Name Sample Library Total peaks High quality autosomal alignments overlapping peaks (%)
Name Sample Library Library description Experiment description ataqv metrics

Using the Plots tab

Using the controls above the plots

  • Hover over samples to highlight samples in the plot.
  • Click samples to toggle sample visibility in the plot.
  • Use the "Search Plot Items" box to filter plot contents. Your input is searched in experiments' names, sample names, and descriptions.

Using the plots

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 their names.
  • Click plot dots or lines to see experiment details.

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.