Statistical inference in a two-compartment model for hematopoiesis

Biometrics. 2001 Jun;57(2):546-53. doi: 10.1111/j.0006-341x.2001.00546.x.

Abstract

We present a method for parameter estimation in a two-compartment hidden Markov model of the first two stages of hematopoiesis. Hematopoiesis is the specialization of stem cells into mature blood cells. As stem cells are not distinguishable in bone marrow, little is known about their behavior, although it is known that they have the ability to self-renew or to differentiate to more specialized (progenitor) cells. We observe progenitor cells in samples of bone marrow taken from hybrid cats whose cells contain a natural binary marker. With data consisting of the changing proportions of this binary marker over time from several cats, estimates for stem cell self-renewal and differentiation parameters are obtained using an estimating equations approach.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Animals
  • Bone Marrow Cells / cytology
  • Cats
  • Colony-Forming Units Assay
  • Glucosephosphate Dehydrogenase / genetics
  • Hematopoiesis*
  • Hematopoietic Stem Cell Transplantation
  • Hematopoietic Stem Cells / cytology
  • Hematopoietic Stem Cells / physiology
  • Humans
  • Markov Chains
  • Models, Biological
  • Phenotype
  • Probability
  • Time Factors

Substances

  • Glucosephosphate Dehydrogenase