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The pipeline performs Fit-hi-c analysis with fixed size windows. The pipeline consists of two stages: mapping_all and hic_pipeline. In mapping_all: runall: This script calls all the other steps below in mapping/filtering pipeline pipeline: This script defines all the variables and a step to be run with runall step1_align: Align the reads using BWA to the reference genome. You will need the appropriate BWA index file. step2_sort: Filter for number of mismatches, mapping quality and unique mapping. step3_joinAllCombinations: Take a join of the separately mapped XYZ_1.fq.gz and XYZ_2.fq.gz files to get paired reads. step3_removePCRdups: Remove the read pairs that map to exactly same coordinates (both ends). Keep only one pair out of many copies. In hic-pipeline: Assignment to fixed size windowing. Process genome for mappability. Then, the normalization using ICE and applying Fit-Hi-C. This pipeline assumes that there are read pairs under the cleanedPairs folders. In pipeline: runall: This script calls all the other steps below step1 in runall: create all the fixed size fragements. Step1 needs to be run only once for a given resolution/window size. Runs intractively In bin: step2_get-contactCounts-atFixedWindowSize: get contacts at fixed window size step3_preprocess_for_bias_pipeline.sh: preprocess the genome to get mappability per window. Note: needs to be run only once for a particular resolution. step4_sparseICEnormalize: normalizes each library using sparse ICE implementation amd calculate biases for each window. step5-ContactsPerFragment: calculate total numbmer of contacts coming out of each window step6_fithic: perform fit-hic on data before and after ICE. In data/reference_genomes/hg19: chromosome length and HindIII fragmens files. In hic-pipeline_repl_combined: The same as hic-pipeline, but combines replicates in step2. Additional paramenters need to be specified in step 2.
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