deeptools

To perform quality control on ChIP-seq data, this Skill uses deepTools to run correlation, PCA, and fingerprint analysis for assessing sample quality. It processes high-throughput sequencing data to generate these comprehensive quality metrics.

Yes, you can convert BAM files to bigWig tracks for NGS visualization. This Skill processes high-throughput sequencing data, supporting normalization methods like RPGC, CPM, and RPKM to prepare tracks for visualizing signals around regions of interest.

The best way to generate heatmaps and profile plots for ATAC-seq data is through this Skill's visualization features. It leverages deepTools to create heatmaps, profile plots, and enrichment analysis for the visual representation of NGS data.

Yes, this Skill supports RNA-seq normalization and sample comparison. It normalizes NGS data using RPGC, CPM, and RPKM methods, and compares samples by generating log2 ratio tracks to identify differences across high-throughput sequencing experiments.

Yes, you need deepTools installed because this Skill requires it for processing and analyzing high-throughput sequencing data. It depends on the deepTools framework to execute its quality control, normalization, comparison, and visualization functions.