The phrase "a perceived cluster" is correct and usable in written English.
It can be used when discussing a group or collection of items, ideas, or phenomena that are recognized or interpreted as being related or connected in some way, often subjectively.
Example: "In the study, researchers identified a perceived cluster of symptoms that were commonly reported by patients."
Alternatives: "an observed grouping" or "a recognized set".
If the a priori perceived cluster pertained to a specific site or category (e.g. brain tumors or leukemia), the cluster was considered confirmed in the presence of a documented statistically significant increase for that cancer site or category.
Verified duplicate files from replicate sequencing were removed from the pool to reduce perceived cluster depth and improve data analysis.
It is clear from Table 1 that some states (e.g. Illinois and Texas) conducted multiple investigations of perceived clusters for a wide array of cancers.
The only category reported with greater frequency was the generic "all cancers" which accounted for 281 of the perceived clusters.
Investigations were categorized with respect to cancer type(s), hypothesized exposure, whether perceived clusters were confirmed (e.g. by elevated incidence), and conclusions about a link between cancer(s) of concern and hypothesized environmental exposure(s).
When evaluating reports from Texas, perceived clusters were considered "confirmed" when the agency stated in the report that the cluster warranted further investigation or observation (even though in some cases further investigation was proposed without clear evidence of elevated disease rates).
The second assessment criterion was whether or not the study was undertaken in response to a perceived cancer cluster in the community.
Much of the research has been conducted in response to such concerns, either based solely on the exposure source or based on a perceived cancer cluster among persons living in the vicinity.
Based on these analyses, investigators will be able to perceive clustering of areas with high detection rate of VL.
