SegSeq

[…] x. the mapping rate of clear data ranged from 97.03 to 97.27%, and the genome coverage ranged from 99.83% to 99.85 (additional file : table s5)., for cnv detection, we employed a matlab packet, segseq. only two de novo cnvs were identified in the proband. however, both cnvs were reported as polymorphisms in the database of genomic variants (dgv)., single nucleotide variants (snvs) […]

[…] including insertions, deletions, inversions and translocations of chromosome bands or arms). copy number variations (cnvs) were detected by an in-house program with an algorithm similar to software segseq of broad institute. ebv integrations were also detected by an in-house program. after the variations were detected, annovar was used to do annotation and classification., first, we combine […]

[…] from gatk and further filtered on exon targets and individual sample genotypes were filtered on a genotype quality score of 50. copy-number alterations were detected based on sequence-read depths by segseq; chromosomal rearrangements were detected from clusters of discordantly mapped reads with inferred insert size longer than 1 kb or mapped to different chromosomes. the observation of distinct […]

[…] reads at the genomic coordinate, and then calculate the read counts across sliding or non-overlapping windows (or bins) , , , , yielding the so-called read depth signal. in the case of cnv-seq and segseq , the ratios of the read counts do not require further normalization due to the requirement of a control sample . otherwise, normalization such as gc-content , and mapability correction […]

[…] normal samples according to our panel of normal bams, and a threshold of greater than 1% in the exome aggregation consortium (exac) database., copy number alterations (cnas) were first detected with segseq for 31 wgs, and gatk4 alpha for 283 wes. gistic2.0 was performed to identify significantly amplified or deleted genomic regions. hierarchical clustering was used to identify sample subtypes. […]

[…] genomes project data have been shown to predict accurate copy number values due to its capability of high-resolution cnv calls []. there have been several approaches based on rd, such as maq [, ], segseq [], mrfast [] and cnvnator []. cnvnator can overcome some disadvantages, including unique regions of the genome [, , ], poor breakpoint resolution [, , , ], and detect different sizes of cnvs, […]

[…] toolkit. point mutations were identified by mutect, a bayesian algorithm; short insertions and deletions determined by local assembly. to detect dna copy-number alterations (cnas), we performed segseq11 to infer somatic cna in genomes on the basis of wes reads. copy numbers < 1.5 were considered to indicate deletions, and those > 2.5 were considered amplifications by comparison […]

[…] of computational methods for estimating copy number alterations (cnas). many tools have been developed for estimating cnas from wes data based on paired normal-tumor samples such as cnv-seq [], segseq [], adtex [], contra [], excavator [], exomecnv [], control-freec (control-free copy number caller) [], and cnvseeqer []. for example, varscan2 [] is a computational tool that can estimate […]

[…] were detected using samtools () gatk; cnvs were detected using cnvnator and snvs were detected using varscan (). additionally, svs were identified using breakdancer and a self-method based on the segseq algorithm (,). the pipeline also included purity estimation. filters were then applied to obtain higher confidence results for the identified variants. next, annovar […]