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Fig. 1 | BMC Genomics

Fig. 1

From: NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data

Fig. 1

An exemplary analysis workflow using NucTools. BAM/SAM files with raw mapped reads are converted to BED format (bowtie2bed.pl), processed to obtain nucleosome-sized reads (extend_SE_reads.pl or extend_PE_reads.pl), and split into chromosomes (extract_chr_bed.pl). Usually, a separate directory with chromosome bed files is created for each sample similarly to the HOMER’s approach. Afterwards chromosome-wide occupancies are calculated and averaged using a window size suitable for the following analysis (bed2occupancy_average.pl). Then for each cell type/state, an average profile is calculated based on the individual replicate profiles (average_replicates.pl). After this point several types of analysis can be performed in parallel: Finding stable/unstable regions (stable_nucs_replicates.pl); comparing replicate-averaged profiles in different cell states/types (compare_two_conditions.pl); calculating nucleosome occupancy profiles at individual regions identified based on the intersection of stable/unstable regions or regions with differential occupancy with genomic features such as promoters, enhancers, etc. (extract_rows_occup.pl); calculating the nucleosome repeat length (nucleosome_repeat_length.pl and plotNRL.R); calculating aggregate profiles or visualizing heat maps of nucleosome occupancy at different genomic features (Cluster Maps Builder). The next types of analysis usually involve gene ontology, multiple-dataset correlations and DNA sequence motif analysis, which can be conducted for the genomic regions of interest identified at the previous steps using external software packages

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