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During the process of coding and constant comparison, clusters of codes emerged.
To correct for these differences in cluster size, we created matched comparison clusters as described (earlier, and fig. 2).
By comparison, clusters other than the EMT-GCs exhibit small magnitudes of chromatin and expression changes [see Additional file 6: Figure S3; see Additional file 10: Figure S4].
In comparison, clusters with fewer home births had higher socio-economic scores and were more permanent settlements with better living conditions.
The reverse comparison (clusters absent from the majority of the gut-restricted group but present in the other gut-associated members) revealed several catalytic and transportation-related functions without any discernible pattern.
Finally, the approximate service uptake was calculated as the total attendance from PHC registers, standardized per 100,000 catchment population (total catchment population in the 9 CCT clusters is 637,227; in 22 comparison clusters, 1,385,574).
Similar(50)
For comparison, cluster analysis was also carried out based on the SNP markers that segregated in the seed parent only.
Interestingly, in the case of the iCD versus iUC comparison, clustering was unable to distinguish between iCD and iUC patients.
The risk of injurious falls differed across clusters, and for three out of four, it was significantly higher than in the comparison cluster.
Figure 1 shows an example graph along with optimal solutions for SPLIT CLUSTER EDITING and MONOPOLAR EDITING and, for comparison, CLUSTER EDITING.
In the second multiple comparison clustering, 188 DTGs (142 up- and 46 down-regulated) were obtained (Additional file 13: Table S10), and all were found to be consistent.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com