Some are propped up like jagged mountains with strangely placed peaks and valleys; others, smaller, are flat.
As can be seen in Table 3, the 1608 ChIP-seq peaks fall preferentially in predicted non-coding regions in comparison with randomly placed peaks within the genome.
As expected, more than 90% of the randomly placed peaks were in coding regions (Table 3), since more than 90% of the genome consists of coding regions [ 10].
Custom, in-house Python scripts were written to determine proximity of ChIP-seq peaks to genomic features of interest, such as the predicted TSC of the nearest gene, as well as to generate Monte-Carlo simulations of the data for comparison with randomly placed peaks in the genome.
Factor experiment affected placing time and placing peak velocity (F 1, 22) = 6.6; p<0.05, η2p = 0.2; F(1, 22) = 9.9, p<0.01, η2p = 0.3): placing time increased and placing peak velocity decreased in experiment 6 (Fig. 2).
Placing peak velocity decreased and placing time showed a trend to increase in the conspecific touching task (Table 1 and Fig. 2).
Reach peak deceleration and placing peak velocity decreased in the close-to-conspecific placing task as compared to the close-to-body-shape placing task (Table 1 and Fig. 2).
The placing parameters analyzed were placing time, placing peak velocity and variability (SD) of placing end point along participants' Y and Z axes (YSD and ZSD), i.e. the variability on the receiver's coronal plane.
As compared to the body-shape placing task, the conspecific feeding task showed an increase in percentage of reach deceleration time, and placing time, and a decrease in placing peak velocity (Table 1 and Fig. 2).
However, in all the experiments the presence of the conspecific induced a decrease in placing peak velocity even when the sequence was directed to another final target (experiments 2 and 3).
