What is a High Density (HD) search

eArray has a special, separate probe database that contains probes that cover the genomes of several species at extremely high densities. These probes are called High Density (HD) probes. A High Density (HD) Search, also known as a zoom-in search, retrieves HD probes from this database for use in CGH (comparative genomic hybridization) and ChIP (chromatin immunoprecipitation) microarrays. The available species vary by application type, and Agilent periodically adds support for additional species. To view a list of currently available species, see the Species search criterion when you set up an HD probe search. The probes in the HD database have been annotated and scored, which allows algorithms to select optimal, Tm-balanced probes.

To search for either HD-CGH or HD-ChIP probes, you specify the exact chromosomal regions(s) or cytobands that are associated with the desired probes. For HD-CGH probes you can also specify gene annotations (such as accessions or gene symbols) for filtering a subset of probes from all the probes in the database.

A Standard HD Search lets you search for probes based on chromosomal location, and lets you apply filters and set the desired probe spacing across all intervals. The result of a Standard HD Probe Search is a balanced probe density across all selected intervals.

In an Advanced HD Search, you enter the probe density and certain filtering characteristics for each genomic interval separately. eArray selects probes independently for each interval, even when intervals overlap. An Advanced HD Probe Search takes more time, and the probe density for each of the selected intervals can differ.

Additional guidance from Agilent

Overall, probes generated using the ‘Genomic Tiling’ function will perform more poorly than probes found in the Agilent HD-CGH Probe Database. Agilent very strongly recommends using the Agilent HD-CGH Probe Database and not the ‘Genomic Tiling’ option. Only for regions where there are not enough HD probes available in the database should ‘Genomic Tiling’ be considered.

All HD probes in the database (except for probes in regions in which no optimal T_m probes exist) have been T_m matched and have a predicted performance score (based on T_m, GC content, a hairpin ΔG, sequence complexity, and metrics to measure homology with the rest of the reference genome). The eArray pair-wise reduction algorithm will pick the best HD probes based on the user-selected average HD probe spacing per interval or the total number of HD probes.

Additionally, during design the HD probes have passed a Tm filter, are annotated such that a user can choose between different similarity filtering options (non-unique probe filter, perfect match filter, or similarity score filter), and if there are catalog probes present in search results they can be preferentially selected. In contrast, using eArray’s ‘Genomic Tiling’ feature probes are picked at a fixed spacing and there is no chance to Tm balance or optimize probes selected for by performance. Probes created should perform no better than those picked at random. The only options to improve probe performance are probe trimming and skipping of repeat masked regions.

See the figure below for an example of CGH data from Agilent HD-CGH probes compared to ‘Genomic Tiling’ probes. The median log2 ratios of the HD-CGH probes are closer to the expected value of -1 with a smaller spread when compared to the ‘Genomic Tiling’ probes.

For probes selected using the Agilent HD-CGH Probe Database:

All HD probes in the database have been designed to avoid repeat masked regions, are T_m matched (except for probes in regions in which no optimal T_m probes exist) and have a predicted performance score (based on T_m, GC content, a hairpin ΔG, sequence complexity, and metrics to measure homology with the rest of the reference genome). The eArray pair-wise reduction algorithm will pick the best HD probes based on the user-selected average HD probe spacing per interval or the total number of HD probes. Additionally, HD probes can be filtered using a T_m filter, similarity filter (non-unique probe filter, perfect match filter, or similarity score filter), or catalog probes can be preferentially selected.
For probes selected using ‘Genomic Tiling’:

Probes in GC-rich, high-T_m, and repeat regions can be very problematic. The only options in ‘Genomic Tiling’ are probe trimming and skipping of repeat masked regions. The new probe set can be further improved by filtering out high-T_m or GC-rich probes. T_m and GC% can be obtained from eArray by using the Score Custom Probes utility under the Probe tab. A probe search using the passing probe IDs can then be used to create a new Probe Group.

When ‘No Filter’ is selected any probe may be selected, regardless of similarity to other genomic sites. Keep in mind that data from “non-unique” probes will be harder to interpret, and it can be beneficial to limit the maximum number of perfect genomic hits by using the Non-Unique Probe Filter option.

When the Perfect Match Filter (or when the maximum number of perfect genomic hits is set to 1 in the Non-Unique Probe Filter) is selected, probes with more than one perfect match to the genome are excluded and as a result it will not be possible to find probes in Segmental Duplication or Pseudo-Autosomal Regions (PAR).

The Similarity Score Filter is the most stringent filter. This filter excludes probes with significant similarity to other sites in the genome and there will be genomic regions where no probes can be found.

Using the Include Regions and selecting Exonic will limit the probes returned to those marked as overlapping exons only. This will work when searching by genomic intervals or gene annotations (transcript and gene identifiers). The designer should be aware that exons typically are more GC-rich than the rest of the genome, these probes, in general, will have a lower probe scores. See the FAQ ”What is a CGH probe score?” for more information. Using this “Exonic” approach there is no possibility to select the nearest probes in introns instead.
Identify the coordinates for the exons outside of eArray and use them as Genomic Intervals to select probes in. Then with the “Extended Interval Boundary” option in eArray the Genomic Intervals can be extended beyond the exon boundaries with a selected number of base pairs. Here are the instructions on how to identify coordinates for exons in UCSC.

Using the Table Browser utility from the UCSC genome browser, make sure the proper species and genome build are selected from the drop-down lists. It is important that the build matches eArray. For “track”, select desired gene definition track, Agilent recommends “CCDS”, “RefSeq Genes”, or “UCSC genes”. Follow the UCSC instructions on how to restrict the search. Options include filtering on genomic regions or track identifiers (names/accessions). Make sure the output contains chrom, exonStarts and exonEnds. This will give you all of the exon coordinates for the regions you defined.

To input these locations into an eArray HD Probe Search, split the line into pieces (one for each exon) and adjust the start coordinate (the output is 0-based, eArray expects 1-based). The orientation (i.e., strand information) does not matter in an eArray probe search. For example, the following line defining three exons (chrom; exon count; exon starts; exon ends):

chr1; 3; 2450045, 2451144, 2451409; 2451048, 2451310, 2451544

Can be converted to the format needed in eArray.:

chr1:2450046-2451048
chr1:2451145-2451310
chr1:2451410-2451544

What is a High Density (HD) search?

Additional guidance from Agilent