Computational protocol: Spatial Colocalization of Human Ohnolog Pairs Acts to Maintain Dosage-Balance

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Protocol publication

[…] For each chromatin conformation capture (Hi-C) dataset, a chromatin interaction matrix was created using the following procedures. Hi-C reads were aligned to the reference genome using Bowtie 2.1.0 () with default parameter settings, and an algorithm that iteratively increases the truncation length (20 bp) to maximize the yield of valid Hi-C interactions was adopted (; ). We retained for further analysis only pairs of reads with a unique hit of high quality (q > 30) at both ends. Subsequent analyses were performed to remove invalid read pairs. The reference genome was divided into restriction fragments by conceptually cutting them at the HindIII enzyme restriction site “AAGCTT” and this process yielded 830,194 fragments. Each read pair end was sorted into its corresponding restriction fragment. Nonligation and self-ligation products that were recognized by restriction fragment and mapping orientation were filtered (). Other invalid read pairs were all removed (Diagonal, StartNearRsite, PCR amplification, random break, LargeSmallFragments, and ExtremeFragments were filtered with the default parameter settings in hiclib) (; ). The quantity of the Hi-C reads after filtering in the human cell lines is listed in supplementary table S1, Supplementary Material online. We then partitioned the human genome into nonoverlapping 500 kb windows and referred to the number of filtered read pairs in the windows as the corresponding contact count of the bins (supplementary table S1, Supplementary Material online). […]

Pipeline specifications

Software tools Bowtie, hiclib
Applications Hi-C analysis, 3C-seq analysis
Organisms Mus musculus, Homo sapiens