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Yang X.,Broad Institute | Chockalingam S.P.,Indian Institute of Technology Bombay | Aluru S.,Iowa State University
Briefings in Bioinformatics | Year: 2013

Error Correction is important for most next-generation sequencing applications because highly accurate sequenced reads will likely lead to higher quality results. Many techniques for error correction of sequencing data from next-gen platforms have been developed in the recent years. However, compared with the fast development of sequencing technologies, there is a lack of standardized evaluation procedure for different error-correction methods, making it difficult to assess their relative merits and demerits. In this article, we provide a comprehensive review of many error-correction methods, and establish a common set of benchmark data and evaluation criteria to provide a comparative assessment. We present experimental results on quality, run-time, memory usage and scalability of several error-correction methods. Apart from providing explicit recommendations useful to practitioners, the review serves to identify the current state of the art and promising directions for future research. Availability: All error-correction programs used in this article are downloaded from hosting websites. The evaluation tool kit is publicly available at: http://aluru-sun.ece.iastate.edu/doku.php?id=ecr. © The Author 2012. Published by Oxford University Press. Source

Daley G.Q.,Howard Hughes Medical Institute | Daley G.Q.,Harvard University | Daley G.Q.,Broad Institute | Daley G.Q.,Harvard Stem Cell Institute
Cell | Year: 2012

The 2012 Nobel Prize in Medicine or Physiology recognizes the architects of two of the great paradigm-shifting discoveries of the last half-century of biology. In experiments performed nearly 50 years apart, Gurdon and Yamanaka made feasible the reawakening of pluripotency inherent in all cells and challenged forever our notions of cellular identity. © 2012 Elsevier Inc. Source

Panagiotou O.A.,University of Ioannina | Panagiotou O.A.,U.S. National Institutes of Health | Willer C.J.,University of Michigan | Hirschhorn J.N.,Center for Basic and Translational Obesity Research | And 3 more authors.
Annual Review of Genomics and Human Genetics | Year: 2013

Meta-analysis of multiple genome-wide association (GWA) studies has become common practice over the past few years. The main advantage of this technique is the maximization of power to detect subtle genetic effects for common traits. Moreover, one can use meta-analysis to probe and identify heterogeneity in the effect sizes across the combined studies. In this review, we systematically appraise and evaluate the characteristics of GWA meta-analyses with 10,000 or more subjects published up to June 2012. We provide an overview of the current landscape of variants discovered by GWA meta-analyses, and we discuss and assess with extrapolations from empirical data the value of larger meta-analyses for the discovery of additional genetic associations and new biology in the future. Finally, we discuss some emerging logistical and practical issues related to the conduct of meta-analysis of GWA studies. Copyright © 2013 by Annual Reviews. All rights reserved. Source

Cherry A.B.C.,Dana-Farber Cancer Institute | Cherry A.B.C.,Harvard University | Cherry A.B.C.,Harvard Stem Cell Institute | Daley G.Q.,Dana-Farber Cancer Institute | And 4 more authors.
Annual Review of Medicine | Year: 2013

The conversion of somatic cells into pluripotent cells is transforming the way diseases are researched and treated. Induced pluripotent stem (iPS) cells' promise may soon be realized in the field of hematology, as hematopoietic stem cell transplants are already commonplace in clinics around the world. We provide a current comparison between induced pluripotent and embryonic stem cells, describe progress toward modeling hematological disorders using iPS cells, and illustrate the hurdles that must be overcome before iPS cell therapies will be available in clinics. Copyright © 2013 by Annual Reviews. Source

Li H.,Broad Institute | Homer N.,University of California at Los Angeles
Briefings in Bioinformatics | Year: 2010

Rapidly evolving sequencing technologies produce data on an unparalleled scale. A central challenge to the analysis of this data is sequence alignment, whereby sequence reads must be compared to a reference. A wide variety of alignment algorithms and software have been subsequently developed over the past two years. In this article, we will systematically review the current development of these algorithms and introduce their practical applications on different types of experimental data. We come to the conclusion that short-read alignment is no longer the bottleneck of data analyses. We also consider future development of alignment algorithms with respect to emerging long sequence reads and the prospect of cloud computing. © The Author 2010. Published by Oxford University Press. Source

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