Figure 1
Figure 1. Identification of candidate gene/SNVs in the thrombocytosis cohort. (A) Workflow schema detailing phenotypic cohorts that were genetically studied (sample numbers in parentheses; BLVRBS111L [462C→T] mutant number in brackets) and output SNVs at critical validation and genetic association steps. NL, healthy controls. (B) Schema delineating computational pipeline with algorithmic filtering analyses at critical steps of genetic bioinformatics processing. (C) Heat map was generated using expression profiles21 for the candidate gene subset (N = 29) encompassing oligonucleotide probes on the Affymetrix HG_U133AAofAv2 array (scale bar on right). (D) Hematopoietic lineage schema is displayed as a Wilcoxon signed-rank test of the t statistic (−log10 P) calculating the likelihood that the 29 member gene subset is more greatly expressed relative to all other genes expressed in ≥1 time point by lineage (scale bar on right).

Identification of candidate gene/SNVs in the thrombocytosis cohort. (A) Workflow schema detailing phenotypic cohorts that were genetically studied (sample numbers in parentheses; BLVRBS111L [462C→T] mutant number in brackets) and output SNVs at critical validation and genetic association steps. NL, healthy controls. (B) Schema delineating computational pipeline with algorithmic filtering analyses at critical steps of genetic bioinformatics processing. (C) Heat map was generated using expression profiles21  for the candidate gene subset (N = 29) encompassing oligonucleotide probes on the Affymetrix HG_U133AAofAv2 array (scale bar on right). (D) Hematopoietic lineage schema is displayed as a Wilcoxon signed-rank test of the t statistic (−log10 P) calculating the likelihood that the 29 member gene subset is more greatly expressed relative to all other genes expressed in ≥1 time point by lineage (scale bar on right).

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