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ELDA: extreme limiting dilution analysis for comparing depleted and enriched populations in stem cell and other assays.

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TLDR
ELDA is a software application for limiting dilution analysis (LDA), with particular attention to the needs of stem cell assays, which is the first limiting dilutions analysis software to provide meaningful confidence intervals for all LDA data sets, including those with 0% or 100% responses.
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This article is published in Journal of Immunological Methods.The article was published on 2009-08-15. It has received 1645 citations till now.

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Endothelial and perivascular cells maintain haematopoietic stem cells

TL;DR: HSCs reside in a perivascular niche in which multiple cell types express factors that promote HSC maintenance, and were depleted from bone marrow when Scf was deleted from endothelial cells or leptin receptor (Lepr)-expressing periv vascular stromal cells.
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Normal and neoplastic nonstem cells can spontaneously convert to a stem-like state

TL;DR: It is demonstrated that normal and CSC-like cells can arise de novo from more differentiated cell types and that hierarchical models of mammary stem cell biology should encompass bidirectional interconversions between stem and nonstem compartments.
References
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Book

Generalized Linear Models

TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
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A Simple Sequentially Rejective Multiple Test Procedure

TL;DR: In this paper, a simple and widely accepted multiple test procedure of the sequentially rejective type is presented, i.e. hypotheses are rejected one at a time until no further rejections can be done.
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Generalized Linear Models

TL;DR: In this paper, the authors used iterative weighted linear regression to obtain maximum likelihood estimates of the parameters with observations distributed according to some exponential family and systematic effects that can be made linear by a suitable transformation.
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Generalized linear models. 2nd ed.

TL;DR: A class of statistical models that generalizes classical linear models-extending them to include many other models useful in statistical analysis, of particular interest for statisticians in medicine, biology, agriculture, social science, and engineering.
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