NDLI: Visualisation of “High p, Small n” data

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J. E. Gentle, W. Härdle, and Y. Mori (eds): Handbook of computational statistics: concepts and methods : Springer, Berlin, 2004, xii + 1070 pp., $299 (paperback)

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Visualisation of “High p, Small n” data

Content Provider	Springer Nature Link
Author	Pittelkow, Y. E. Wilson, S. R.
Copyright Year	2007
Abstract	Development of methods for visualisation of high-dimensional data where the number of observations, n, is small compared to the number of variables, p, is of increasing importance. One major application is the burgeoning field of microarray (gene expression) experiments. Because of their high cost, the number of chips (n) is O(10 − 102) while the number (p) of genes (including expressed sequence tags) on each chip is O(103 − 104). Based on synthetic data simulated in accord with current biological interpretation of microarray data, we have adapted the biplot that simultaneously plots the genes and the chips to display relevant experimental information. Other ordination techniques are also useful for visually exploring microarray data. The biological information that can be revealed by applying these exploratory, visual techniques is illustrated using data from gene expression experiments. When ordination methods, or dimension reduction methods such as PCA and its many variants, are used, in association with gene selection methods, it is well known that “selection bias” can result. We show an application of bootstrap methodology to ordination methods that can be used to account for this bias. Such methods are invaluable when visualization methods are used for pattern recognition, such as when identifying previously unknown sub-classes of tumours in molecular classification.
Starting Page	533
Ending Page	541
Page Count	9
File Format	PDF
ISSN	09434062
Journal	Computational Statistics
Volume Number	22
Issue Number	4
e-ISSN	16139658
Language	English
Publisher	Springer-Verlag
Publisher Date	2007-11-20
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Economic Theory Probability Theory and Stochastic Processes Probability and Statistics in Computer Science Statistics
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty Computational Mathematics

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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