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- Anil, Anandashankar, et al.
(författare)
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HiCapTools : a software suite for probe design and proximity detection for targeted chromosome conformation capture applications
- 2018
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Ingår i: Bioinformatics. - : OXFORD UNIV PRESS. - 1367-4803 .- 1367-4811. ; 34:4, s. 675-677
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Tidskriftsartikel (refereegranskat)abstract
- Folding of eukaryotic genomes within nuclear space enables physical and functional contacts between regions that are otherwise kilobases away in sequence space. Targeted chromosome conformation capture methods (T2C, chi-C and HiCap) are capable of informing genomic contacts for a subset of regions targeted by probes. We here present HiCapTools, a software package that can design sequence capture probes for targeted chromosome capture applications and analyse sequencing output to detect proximities involving targeted fragments. Two probes are designed for each feature while avoiding repeat elements and non-unique regions. The data analysis suite processes alignment files to report genomic proximities for each feature at restriction fragment level and is isoform-aware for gene features. Statistical significance of contact frequencies is evaluated using an empirically derived background distribution. Targeted chromosome conformation capture applications are invaluable for locating target genes of disease-associated variants found by genome-wide association studies. Hence, we believe our software suite will prove to be useful for a wider user base within clinical and functional applications.
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| 2. |
- Björn, Niclas, et al.
(författare)
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Comparison of Variant Calls from Whole Genome and Whole Exome Sequencing Data Using Matched Samples
- 2018
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Ingår i: Journal of Next Generation Sequencing & Applications. - 2469-9853. ; 5:1, s. 1-8
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Tidskriftsartikel (refereegranskat)abstract
- Whole exome sequencing (WES) has been extensively used in genomic research. As sequencing costs decline it is being replaced by whole genome sequencing (WGS) in large-scale genomic studies, but more comparative information on WES and WGS datasets would be valuable. Thus, we have extensively compared variant calls obtained from WGS and WES of matched germline DNA samples from 96 lung cancer patients. WGS provided more homogeneous coverage with higher genotyping quality, and identified more variants, than WES, regardless of exome coverage depth. It also called more reference variants, reflecting its power to call rare variants, and more heterozygous variants that met applied quality criteria, indicating that WGS is less prone to allelic drop outs. However, increasing WES coverage reduced the discrepancy between the WES and WGS results. We believe that as sequencing costs further decline WGS will become the method of choice even for research confined to the exome.
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