ChIP-Seq and ATAC-Seq identify enriched regions or peaks in genome. Depending on the assay, the biological meaning of enrichment changes; in ChIP-Seq, enrichment indicates protein binding, while in ATAC-Seq, enrichment indicates open chromatin. To understand the importance of enriched regions in regulating gene expression, we can add information about overlapping or nearby genomic features.
Annotate peaks takes an input set of regions and checks for overlap between those regions and a gene/feature annotation. This gives regulatory context for enriched regions.
The input for Annotate peaks is a Peaks type data node.
Click a Peaks data node
Click the Peak analysis section in the toolbox
Click Annotate peaks
Set the Genomic overlaps parameter
The Genomics overlaps parameter lets you choose one of two options (Figure 1).
Report one gene region per peak (precedence applies) chooses one gene section for each peak using the precedence order to settle cases where more than one gene section overlaps a peak. The order of precedence is TSS, TTS, CDS Exon, 5' UTR Exon, 3' UTR Exon, Intron, Intergenic.
Report all gene regions per peak creates a row for each gene section that overlaps a peak in the task report. \
User should define the transcription start site (TSS) and transcription termination site (TTS) limit in the unit of bp
Choose a gene/feature annotation from the drop-down menu
Click Finish to run
Annotate peaks produces an Annotated peaks data node. The Annotated peaks task report adds a Gene section breakdown pie chart and adds columns with information about the _Gene ID_s, _Transcript ID_s, Gene section, Distance to TSS, and Distance to TTS of each peak to the standard Peaks report (Figure 2). If run with the option to report all gene sections selected, each peak will have a row for each gene section it overlaps. If run with the option to report one gene section selected, each peak will have one row with the gene section it overlaps chosen using the order of precedence.
The table can be sorted by any of its columns (Figure 3). Click on the Optional columns on the upper-left corner of the table to add more information on each region
\
TSS
Transcription start site (TSS) is -1000bp and +100bp (default setting) from the TSS for a transcript
TTS
\
Transcription termination site (TTS) is -100bp and +1000bp (default setting) from the TTS for a transcript
CDS Exon
Coding sequence (CDS) Exon is overlapping a coding exon in a transcript
5' UTR Exon
5' Untranslated Region (UTR) Exon is overlapping an exon in the 5' UTR of a transcript
3' UTR Exon
3' Untranslated Region (UTR) Exon is overlapping an exon in the 3' UTR of a transcript
Intron
Intron is overlapping an intron in a transcript
Intergenic
Intergenic is not located within 1000bp of a transcript
If you need additional assistance, please visit our support page to submit a help ticket or find phone numbers for regional support.
Peak region detection is performed on each sample respectively. The peak regions can be analyzed across samples. Partek Flow provides tools necessary to interrogate and prioritize regions for further analysis.
If you need additional assistance, please visit our support page to submit a help ticket or find phone numbers for regional support.
After peak detection, you can filter peaks or annotated peaks to generate peaks of interest for downstream analysis.
The input for this task is a peaks-type data node.
Choose a Peaks data node
Click Filter peaks task in Peak analysis section in the pop-up menu (Figure 1)
The first drop-down menu allows you to choose to include or exclude base on the specified criteria.
The second drop-down menu allows you to choose any categorical or numeric information of the peaks to use for the filter criteria.
When you choose Sample name, or Chromosome, which are categorical information, the third drop-down menu will have is and is not as options. The fourth drop-down menu allows you to choose from the subgroups of the information (Figure 2).
When you select other information in the 2nd drop-down list, like Start, End, Length, Absolute summit, Pileup, -log10(pvalue), Fold enrichment or -log10(qvalue), which is numeric, the third drop-down includes:
<: less than
<=: less than or equal to
==: equal to
>: greater than
>=: greater than or equal to
The threshold is set using the text box (Figure 3). The input must be a number.\
When use OR and AND operators, you can build more advanced filter criteria:
When combining multiple filters all set to Include:
With AND, if all statements must be true for the sample to meet the filter criteria.
With OR, if any statement is true, the sample will meet the filter criteria.
When combining multiple filters all set to Exclude:
With AND, if any statement is true, the sample will meet the filter criteria.
With OR, all statements must be true for the sample to meet the filter criteria.
When you invoke filter peak task on a transcript/gene annotated peak data node, there is an additional option to filter peak regions based on a list of transcripts or genes (Figure 4).
Please see the Feature list filter chapter here.
The Annotate regions task in Flow labels individual peaks as promoters for a particular gene if the peak falls 1000 bases upstream from a gene's transcription start site, or 1000 bases downstream from a gene's transcription start site by default. A promoter sum for a given gene is the number of cut sites per cell that fall within all the peaks labeled as promoters (-1000bp ~ 1000bp by default or user defined through Annotate regions) for that gene. Higher promoter sum values indicate higher chromatin accessibility in the promoter region [1].
Flow task Promoter sum matrix summarizes each promoter sum and outputs a cell x gene matrix. In the matrix, only genes that have peaks within its promoter region have been included. In Flow Promoter sum matrix can be invoked in the Peak analysis section by clicking the Annotated regions data node (Figure 1).
To run Promoter sum matrix in Flow,
Click the Annotated regions data node
Click the Peak analysis section in the toolbox
Click Promoter sum matrix
Once the task has been finished, a new data node will be produced where the promoter sum value for each feature can be used to color UMAP/T-SNE and to determine cell type (Figure 2).
If you need additional assistance, please visit our support page to submit a help ticket or find phone numbers for regional support.
