Package: changeseq
CHANGE-seq: Circularization for High-throughput Analysis Nuclease Genome-wide Effects by SequencingThis is a repository for CHANGE-seq analytical software, which takes sample-specific paired-end FASTQ files as input and produces a list of CHANGE-seq detected off-target cleavage sites as output.SummaryThis package implements a pipeline that takes in reads from the CHANGE-seq assay and returns detected cleavage sites as output. The individual pipeline steps are:Merge: Merge read1 an read2 for easier mapping to genome.Read Alignment: Merged paired end reads from the assay are aligned to the reference genome using the BWA-MEM algorithm with default parameters (Li. H, 2009).Cleavage Site Identification: Mapped sites are analyzed to determine which represent high-quality cleavage sites.Visualization of Results: Identified on-target and off-target cleavage sites are rendered as a color-coded alignment map for easy analysis of results.InstallationThe most easiest way to install change-seq pipeline is via conda.conda create -n changeseq -c conda-forge -c bioconda -c anaconda -c omnia -c tsailabSJ changeseq

source activate changeseq

changeseq.py -h

## BWA 0.7.17 and samtools 1.9 are automatically installed

## If Homer is available, the identified off-targets will be annotated using "annotatePeaks.pl", specify the genome version in the YAML file.Alternatively, you can git clone this repository and installgit clone https://github.com/tsailabSJ/changeseq

cd changeseq

pip install -r requirements.txt

python setup.py install

changeseq.py -h

## Please install BWA and samtools if you choose this optionDownload Reference GenomeThe CHANGEseq package requires a reference genome for read mapping. You can use any genome of your choosing, but for all of our testing and original CHANGE-seq analyses we use hg19 (download). Be sure to (g)unzip the FASTA file before use if it is compressed.UsageThe change-seq pipeline requires a manifest yaml file specifying input files, output directory, and pipeline parameters. Once the yaml file is created, users can simply runchange_seq.py all --manifest /path/to/manifest.yamlBelow is an examplemanifest.yamlfile::reference_genome: /data/joung/genomes/Homo_sapiens_assembly19.fasta
analysis_folder: /data/joung/CHANGE-Seq/test2

bwa: bwa
samtools: samtools

read_threshold: 4
window_size: 3
mapq_threshold: 50
start_threshold: 1
gap_threshold: 3
mismatch_threshold: 6
search_radius: 30
merged_analysis: True

samples:
    U2OS_exp1_VEGFA_site_1:
        target: GGGTGGGGGGAGTTTGCTCCNGG
        read1: /data/joung/sequencing_fastq/150902_M01326_0235_000000000-AHLT8/fastq/1_S1_L001_R1_001.fastq.gz
        read2: /data/joung/sequencing_fastq/150902_M01326_0235_000000000-AHLT8/fastq/1_S1_L001_R2_001.fastq.gz
        controlread1: /data/joung/sequencing_fastq/150902_M01326_0235_000000000-AHLT8/fastq/4_S4_L001_R1_001.fastq.gz
        controlread2: /data/joung/sequencing_fastq/150902_M01326_0235_000000000-AHLT8/fastq/4_S4_L001_R2_001.fastq.gz
        description: U2OS_exp1
    U2OS_exp1_EMX1:
        target: GAGTCCGAGCAGAAGAAGAANGG
        read1: /data/joung/sequencing_fastq/150902_M01326_0235_000000000-AHLT8/fastq/2_S2_L001_R1_001.fastq.gz
        read2: /data/joung/sequencing_fastq/150902_M01326_0235_000000000-AHLT8/fastq/2_S2_L001_R2_001.fastq.gz
        controlread1: /data/joung/sequencing_fastq/150902_M01326_0235_000000000-AHLT8/fastq/4_S4_L001_R1_001.fastq.gz
        controlread2: /data/joung/sequencing_fastq/150902_M01326_0235_000000000-AHLT8/fastq/4_S4_L001_R2_001.fastq.gz
        description: U2OS_exp1Quickstartgit clone https://github.com/tsailabSJ/changeseq

cd changeseq/test

changeseq.py all --manifest CIRCLEseq_MergedTest.yamlExample OutputWriting A Manifest FileWhen running the end-to-end analysis functionality of the CHANGEseq package a number of inputs are required. To simplify the formatting of these inputs and to encourage reproducibility, these parameters are inputted into the pipeline via a manifest formatted as a YAML file. YAML files allow easy-to-read specification of key-value pairs. This allows us to easily specify our parameters. The following fields are required in the manifest:reference_genome: The absolute path to the reference genome FASTA file.output_folder: The absolute path to the folder in which all pipeline outputs will be saved.bwa: The absolute path to thebwaexecutablesamtools: The absolute path to thesamtoolsexecutableread_threshold: The minimum number of reads at a location for that location to be called as a site. We recommend leaving it to the default value of 4.window_size: Size of the sliding window, we recommend leaving it to the default value of 3.mapq_threshold: Minimum read mapping quality score. We recommend leaving it to the default value of 50.start_threshold: Tolerance for breakpoint location. We recommend leaving it to the default value of 1.gap_threshold: Distance between breakpoints. We recommend leaving it to the default value of 3 for Cas9.mismatch_threshold: Number of tolerated gaps in the fuzzy target search setp. We recommend leaving it to the default value of 6.read_length: Fastq file read length, default is 151.PAM: PAM sequence, default is NGG.genome: used for homer peak annotation, e.g., hg19, hg38, mm9, or mm10.merged_analysis: Whether or not the paired read merging step should takingTruesamples: Lists the samples you wish to analyze and the details for each. Each sample name should be nested under the top level samples key, and each sample detail should be nested under the sample name. See the sample manifest for an example.For each sample, you must provide the following parameters:target: Target sequence for that sample. Accepts degenerate bases.read1: The absolute path to the .FASTQ(.gz) file containing the read1 reads.read2: The absolute path to the .FASTQ(.gz) file containing the read2 reads.controlread1: The absolute path to the .FASTQ(.gz) file containing the control read1 reads.controlread2: The absolute path to the .FASTQ(.gz) file containing the control read2 reads.description: A brief description of the samplePipeline OutputWhen running the full pipeline, the results of each step are outputted to theoutput_folderin a separate folder for each step. The output folders and their respective contents are as follows:output_folder/aligned: Contains an alignment.sam, alignment.bam, sortedbam, and.baiindex file for each sample.output_folder/fastq: Merged.fastq.gzfiles for each sample.output_folder/identified: Contains tab-delimited.txtfiles for each sample containing the identified DSBs, control DSBs, filtered DSBs, and read quantification.output_folder/visualization: Contains a.svgvector image representing an alignment of all detected off-targets to the targetsite for each sample.FAQHomer installationconda install -c bioconda homer

# To install genome annotation
# Ref: http://homer.ucsd.edu/homer/introduction/configure.html

## Suppose you want to install hg19, follow the command here:

annotatePeaks.pl xxx hg19

## You should be able to see:

!!!!Genome hg19 not found in /rgs01/project_space/tsaigrp/Genomics/common/anaconda3/envs/changeseq/share/homer-4.11-2/.//config.txt

	To check if is available, run "perl /rgs01/project_space/tsaigrp/Genomics/common/anaconda3/envs/changeseq/share/homer-4.11-2/.//configureHomer.pl -list"
	If so, add it by typing "perl /rgs01/project_space/tsaigrp/Genomics/common/anaconda3/envs/changeseq/share/homer-4.11-2/.//configureHomer.pl -install hg19"

## Copy and paste the perl command to install genome annotation