Quality of sequencing was assessed with FastQC v0.11.4 (www.bioinformatics.babraham.ac.uk/projects/fastqc/). Reads having less than 80% of quality scores above 25 were removed with NGSQCToolkit v2.3.3 (47) using the command IlluQC.pl -se $file_path N A -l $percent -s $threshold -p $nb_cpu -o $out_path. Reads were aligned to the human hg19 reference genome from Illumina iGenomes University of California, Santa Cruz (UCSC) collection using bowtie v1.0.0 (48), allowing three mismatches and keeping uniquely aligned reads (bowtie -q -v 3 -p $nb_cpu -m 1 -k 1 --best --sam --seed 1 $bowtie_index_path "$file_path"). Sam (sequence alignment/map) outputs were converted to Bam (binary alignment/map) with SAMtools v1.0.6 (49) (samtools view -S -b $file_path -o $out_path/$file_name.bam) and were sorted with Picard tools v1.88 (http://broadinstitute.github.io/picard; java -jar SortSam.jar SO=coordinate I=$input_bam O=$output_bam). Data were further processed with Pasha v0.99.21 (50) with the following parameters: WIGvs = TRUE, incrArtefactThrEvery = 7,000,000, elongationSize = NA (not available). Fixed steps wiggle files were converted to bigwigs, with the script wigToBigWig available on the UCSC Genome Browser website (http://hgdownload.soe.ucsc.edu/admin/exe/).

Spike-in normalization was achieved using Drosophila melanogaster DNA aligned to Illumina iGenomes dm3, as mentioned above (51). Endogenous and exogenous scaling factors were computed from the bam files [1/(number_mapped_reads/1,000,000)]. Endogenous scaling factors were applied to the data before input subtraction (without scaling). The reads per million reads normalization was then reversed before scaling with exogenous factors. The scripts used to perform spike-in scaling was integrated in the Bioconductor package ChIPSeqSpike (https://bioconductor.org/packages/3.7/bioc/html/ChIPSeqSpike.html).

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