## 3 Results
### Gse24850
#### 3.1.1 PCA-Based Unsupervised FE with Optimized SD
\begin{table}
\begin{tabular}{l} \hline \hline
**Names of Methods and Descriptions** \\ \hline MOSAiCS \\ MOSAiCS [28] was implemented as a bioconductor package [29]. Version 2.32.0 was installed in R [30] and applied to GSE24850. MOSAiCS provides biologically motivated statistical models for reads that arise under both non-enrichment (background) and enrichment (signal). Furthermore, MOSAiCS builds a parametric background model that accounts for biases such as GC content and mappability that are inherent to ChIP-seq data. The MOSAiCS model does not assume punctuated or broad peak structures, but instead quantifies whether the ChIP reads show enrichment compared to the background reads for every genomic interval (e.g., bin) of user-defined size in the genome. \\
**DFilter** \\ DFilter [31] was implemented as a Linux command-line program. Ver. 1.6 was downloaded from [[https://reggenlab.github.io/DFilter/](https://reggenlab.github.io/DFilter/)]([https://reggenlab.github.io/DFilter/](https://reggenlab.github.io/DFilter/)) (accessed on 20 August 2023). DFilter takes as input a set of sequence tags mapped to a reference genome. Based on the genomic distribution of tags, the algorithm classifies individual \(n\)-base-pair bins as positive (signal) or negative (noise) regions. DFilter implements linear finite-impulse-response detection, that is, a windowed linear filter \(h\) of user-specified width, followed by the standard thresholding step. \\
**F-Seq2** [32] was implemented as a Linux command-line program. It was downloaded from [[https://github.com/Boyle-Lab/F-Seq2](https://github.com/Boyle-Lab/F-Seq2)]([https://github.com/Boyle-Lab/F-Seq2](https://github.com/Boyle-Lab/F-Seq2)) (accessed on 20 August 2023). F-Seq2 employed the Gaussian kernel density function to quantify the amount of protein binding. The total control read count was linearly scaled to be equal to the total treatment read count at the individual chromosome level, as the ratios of total reads fluctuated between different chromosomes. \\
**HOMER** \\ HOMER [33] was implemented as a Linux command-line program. The latest version, HOMER 4.11, which was released on 24 October 2019, was downloaded from [[http://homer.ucsd.edu/homer/](http://homer.ucsd.edu/homer/)]([http://homer.ucsd.edu/homer/](http://homer.ucsd.edu/homer/)) (accessed on 20 August 2023). For each ChIP-seq experiment, ChIP-enriched regions (peaks) were found by first identifying significant clusters of ChIP-seq tags and then filtering these clusters for those that were significantly enriched relative to background sequencing and local ChIP-seq signal. \\
**RSEG** \\ RSEG [34] was implemented as a Linux command-line program. The latest version, 0.4.9, was downloaded from [[http://smithlabresearch.org/software/rseg/](http://smithlabresearch.org/software/rseg/)]([http://smithlabresearch.org/software/rseg/](http://smithlabresearch.org/software/rseg/)) (accessed on 20 August 2023). The negative binomial distribution is assumed to quantify the amount of protein binding between control and treated samples using the NBDiff distribution, which is the discrete distribution of the difference between two independent negative binomial random variables. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The list of methods used for the comparison with the present study. the enriched histone modification associated with adjusted \(p\)-values of less than 0.05. All were H3K9 me3 modifications, suggesting that the proposed method was successful. In addition, 5 out of 10 were brain-related, which was coincident with GSE24850 comprising experiments that used the nucleus accumbens, strengthening the success of the proposed method.