In this paper, we introduce TopPG, a proteogenomic tool for generating proteoform sequence databases with genetic alterations and alternative splicing events. However, top-down proteogenomics, in which genomic or transcriptomic data are combined with top-down mass spectrometry data, has not been widely adopted, and there is still a lack of software tools for top-down proteogenomic data analysis. In the last decade, top-down mass spectrometry has attracted increasing attention because of its capacity to identify various proteoforms with alterations. Most proteogenomic research has been focused on combining genomic or transcriptomic data with bottom-up mass spectrometry data. Variant Quality Score Recalibration (VQSR) is performed using dbSNP138 so quality metrics for each variant can be used in downstream variant filtering.In proteogenomic studies, genomic and transcriptomic variants are incorporated into customized protein databases for the identification of proteoforms, especially proteoforms with sample-specific variants. Single nucleotide variants and Indels are called using GATK HaplotypeCaller (v3.5), which generates a single-sample GVCF. Data are further processed using the GATK best-practices (v3.5), which generates VCF files in the 4.2 format. Sequencing reads were aligned to the human reference, hs38DH, using BWA-MEM v0.7.15. Our automated analysis pipeline for whole genome sequencing matches the CCDG and TOPMed recommended best practices. We believe this instrument represents the future for WGS with short-read technology, and it was important to sequence the 1KG samples in a format that is consistent with future large scale sequencing projects. We sequenced these samples on the Illumina NovaSeq 6000 sequencing instrument, with 2x150bp reads. Specifically, we generated PCR-free sequencing libraries using unique dual indices to avoid the index switching phenomenon that occurs and causes low level sequencing data contamination on the Illumina patterned flow cells. We processed these samples using the laboratory processes we have previously used for the CCDG project (with minor modifications).
Though a small number of 1KG samples had been sequenced to high coverage previously, we sequenced all samples to depth on the latest technology, providing a unified dataset for the next phase of analyses.
We sequenced all 2,504 samples from the 1000 Genomes (1KG) Project to a minimum of 30x mean genome coverage. 30X whole genome sequencing coverage of the 2504 PhGenome samples.
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