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Pipeline website: http://utap.wexac.weizmann.ac.il

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Then, login to utap.wexac.weizmann.ac.il via Firefox or Chrome (the pipeline is NOT compatible with Internet Explorer) using your Weizmann userID and password and click on "Run pipeline":

1. Click on CHIP-seq in the Choose pipeline box:

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1. Quality control: Reads are trimmed using cutadapt (DOI: 14806/ej.17.1.200) (with the parameters --times 2 -q 20 -m 25). In this process, primers corresponding to the Tru-seq protocol are removed.
2. Quality control: Reads quality control is evaluated using FastQC (with the parameter --cassava). A report file, containing quality results for all of the samples is generated using multiQC.
3. Mapping to genomes: The quality trimmed reads are mapped to Mouse/Human genomes: /shareDB/iGenomes/Mus_musculus/UCSC/mm10/Sequence/Bowtie2Index/genome /shareDB/iGenomes/Homo_sapiens/UCSC/hg19/Sequence/Bowtie2Index/genome, /shareDB/iGenomes/Homo_sapiens/UCSC/hg38/Sequence/Bowtie2Index/genome respectively, using Bowtie2 (doi: 10.1038/nmeth.1923.) (with the parameters --local for all analyses and, in addition, -X 2000 for paired end analyses). Refseq annotation is provided for the mapped genes.
4. Alignment filtering: Following the alignment, reads are filtered using samtools view with the parameters -F 4 to remove unmapped reads that are output by bowtie2, -q 39 and with -f 0x2 for paired end reads. The remaining unique reads are then indexed and sorted, using samtools index and samtools sort.
5. Generation of statistics on the alignment using flagstat.
6. Visualization in graphs: The reads are graphically visualized using ngsplot (with the parameters -G -R genebody -C -O samples -D refseq -L 50000).
7. Peak calling: Significant chip regions (peaks) are evaluated and compared to control samples if present using macs2 callpeak (with the parameters --bw 300 -B -f --SPMR -g -keep-dup auto -q 0.01 for all analyses, BAMPE --nomodel for paired end analyses, and BAM for single end analyses). The resulting peaks "*_peaks_filtered.broadPeak" are filtered to exclude peaks from the blacklist (https://github.com/Boyle-Lab/Blacklist/tree/master/lists).
8. Conversion to BigWig format: Files containing the predicted peaks coordinates in BedGraph format are converted to BigWig format using bedtools slop (with the parameters -g -b 0), bedClip stdin and bedGraphToBigWig (with default parameters)
9. Peak annotation: The predicted peaks are collected from all samples using multiIntersectBed and then annotated according to the corresponding genome using Homer (with default parameters). Analysis of peaks distribution in genomic regions, and around TSS is done using ChipSeeker, together with a Venn diagram of overlap of peaks sets.

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