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Sas statistical software package version 8

Manufactured by SAS Institute
Sourced in United States

SAS statistical software package version 8.2 is a comprehensive data analysis and statistical modeling tool. It provides a wide range of statistical procedures and analytical capabilities to assist users in data management, exploration, modeling, and reporting. The software is designed to handle large and complex datasets, enabling users to perform advanced statistical analyses and generate insightful visualizations.

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Lab products found in correlation

2 protocols using sas statistical software package version 8

1

Allele Frequency Estimation and Genetic Association Analysis

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The genotypic distribution of each marker tested for the association studies was not significantly different from that expected based on the Hardy-Weinberg equilibrium in either the case or control group (SAS Genetics v 8.02). In the initial screening with pooled DNA samples, peak heights of the SNaPshot products in a pool of case DNA and in a pool of control DNA samples were measured. The frequency f of allele A was calculated as f(A)=HA/(HA+kHB), where HA and HB are the peak heights of the SNaPshot products representing alleles A and B. A correction factor (k), the ratio of the peak heights in the heterozygous sample (HA/HB), was used to correct for systematic unequal representation of alleles that occurred with most genotyping methods. This was estimated from 8–16 independent heterozygotes samples that were individually genotyped. The frequency f of allele B was calculated as 1-f(A). Estimated allele frequencies were converted to numbers and were tested for approximate statistical significance by χ2 analysis. For individual genotyping methods, genetic associations were also tested using Pearson χ2-test with the SAS statistical software package version 8.2 (SAS, Cary, NC, USA).
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2

Prognostic Factors in Allogeneic HSCT

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The incidences of aGVHD, cGVHD, leukemia relapse, engraftment, and TRM were evaluated with cumulative incidence curves, taking into account competing risks. Assessments of risk factors for outcomes were calculated by multivariate analysis using Cox proportional hazards regression. The prognostic value of the following variables was investigated: treatment strategy (HRD vs. MSD), patient or donor age (<40 vs. ≥40 years), CD34-positive (+) cells in the graft, mononuclear cells in the graft, Eastern Cooperative Oncology Group (ECOG) score, cytogenetics risk status, molecular abnormalities risk status, CR duration time after the first induction therapy, blasts in peripheral blood before transplantation, blasts in bone marrow before transplantation, donor–recipient sex match, and occurrence of GVHD. Probabilities of survival and DFS were calculated via the Kaplan–Meier method using log-rank tests. Multivariate analyses were conducted to identify independent predictors of NRM, relapse, DFS, and OS. The SAS statistical software package version 8.2 (SAS Institute, Cary, NC, USA) was used for all analyses.
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