ssnr estimation Search Results


ssnr estimation  (MathWorks Inc)
90
MathWorks Inc ssnr estimation
Ssnr Estimation, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/ssnr estimation/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
ssnr estimation - by Bioz Stars, 2026-04
90/100 stars
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subclones  (SciClone Inc)
90
SciClone Inc subclones
Flowchart of GenoClone. VarScan2 is used to detect the somatic mutations (sSNVs) and germline mutations (SNPs) from tumor and matched normal samples. Then, GenoClone detects <t>sSNV–SNP</t> linkage by paired-end reads or long reads to infer the genotype of sSNVs. The observed VAFs are computed from short-read coverage. Finally, GenoClone integrates the genotype of sSNVs and their VAFs in the optimization model to infer subclones.
Subclones, supplied by SciClone Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/subclones/product/SciClone Inc
Average 90 stars, based on 1 article reviews
subclones - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier

Image Search Results


Flowchart of GenoClone. VarScan2 is used to detect the somatic mutations (sSNVs) and germline mutations (SNPs) from tumor and matched normal samples. Then, GenoClone detects sSNV–SNP linkage by paired-end reads or long reads to infer the genotype of sSNVs. The observed VAFs are computed from short-read coverage. Finally, GenoClone integrates the genotype of sSNVs and their VAFs in the optimization model to infer subclones.

Journal: Briefings in Bioinformatics

Article Title: Revealing tumor heterogeneity of breast cancer by utilizing the linkage between somatic and germline mutations

doi: 10.1093/bib/bby084

Figure Lengend Snippet: Flowchart of GenoClone. VarScan2 is used to detect the somatic mutations (sSNVs) and germline mutations (SNPs) from tumor and matched normal samples. Then, GenoClone detects sSNV–SNP linkage by paired-end reads or long reads to infer the genotype of sSNVs. The observed VAFs are computed from short-read coverage. Finally, GenoClone integrates the genotype of sSNVs and their VAFs in the optimization model to infer subclones.

Article Snippet: Although SciClone predicted the same number of subclones, GenoClone showed advantages in estimating the fractions of subclones and identifying sSNV composition of each subclone.

Techniques:

Comparison of GenoClone, PyClone and SciClone in the simulation. (A) The black bar represents the true fractions of the four subclones. The fractions of the subclones inferred by GenoClone (red bars) are closer to the true ones than PyClone (green bars) and SciClone (blue bars). (B) The accuracy of sSNV composition identification of each subclone by GenoClone, SciClone and Pyclone. GenoClone showed the highest accuracy except the Subclone 1.

Journal: Briefings in Bioinformatics

Article Title: Revealing tumor heterogeneity of breast cancer by utilizing the linkage between somatic and germline mutations

doi: 10.1093/bib/bby084

Figure Lengend Snippet: Comparison of GenoClone, PyClone and SciClone in the simulation. (A) The black bar represents the true fractions of the four subclones. The fractions of the subclones inferred by GenoClone (red bars) are closer to the true ones than PyClone (green bars) and SciClone (blue bars). (B) The accuracy of sSNV composition identification of each subclone by GenoClone, SciClone and Pyclone. GenoClone showed the highest accuracy except the Subclone 1.

Article Snippet: Although SciClone predicted the same number of subclones, GenoClone showed advantages in estimating the fractions of subclones and identifying sSNV composition of each subclone.

Techniques: Comparison

Subclone fraction estimation with different sSNV–SNP linkage ratios in the simulation. The true fractions of the four subclones are 0.05, 0.15, 0.35 and 0.45 (dashed lines). The fractions estimated by GenoClone with different sSNV-SNP linkage ratios are close to the true values. As the linkage ratio increases, the variance of fraction estimation decreases.

Journal: Briefings in Bioinformatics

Article Title: Revealing tumor heterogeneity of breast cancer by utilizing the linkage between somatic and germline mutations

doi: 10.1093/bib/bby084

Figure Lengend Snippet: Subclone fraction estimation with different sSNV–SNP linkage ratios in the simulation. The true fractions of the four subclones are 0.05, 0.15, 0.35 and 0.45 (dashed lines). The fractions estimated by GenoClone with different sSNV-SNP linkage ratios are close to the true values. As the linkage ratio increases, the variance of fraction estimation decreases.

Article Snippet: Although SciClone predicted the same number of subclones, GenoClone showed advantages in estimating the fractions of subclones and identifying sSNV composition of each subclone.

Techniques:

Similarities among the subclones from 167 TCGA-BRCA samples. (A) The heatmap of similarity of mutual subclone pairs identified from 167 TCGA-BRCA samples. The P -value of each pair of subclones was calculated by the Fisher’s exact test. The biggest cluster is highlighted by the black solid-line box and the other two clusters are highlighted by the white dashed-line box. (B) The sSNVs in the biggest clusters. The sSNVs occurred at least four times are shown. Chr2_55679588_CA occurs in 10 samples. Chr2_55679588_CA represents the sSNV at chromosome 2 and its position is 55679588 with reference C to A.

Journal: Briefings in Bioinformatics

Article Title: Revealing tumor heterogeneity of breast cancer by utilizing the linkage between somatic and germline mutations

doi: 10.1093/bib/bby084

Figure Lengend Snippet: Similarities among the subclones from 167 TCGA-BRCA samples. (A) The heatmap of similarity of mutual subclone pairs identified from 167 TCGA-BRCA samples. The P -value of each pair of subclones was calculated by the Fisher’s exact test. The biggest cluster is highlighted by the black solid-line box and the other two clusters are highlighted by the white dashed-line box. (B) The sSNVs in the biggest clusters. The sSNVs occurred at least four times are shown. Chr2_55679588_CA occurs in 10 samples. Chr2_55679588_CA represents the sSNV at chromosome 2 and its position is 55679588 with reference C to A.

Article Snippet: Although SciClone predicted the same number of subclones, GenoClone showed advantages in estimating the fractions of subclones and identifying sSNV composition of each subclone.

Techniques: