LRpath - Pathway Analysis using Logistic Regression
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The NCIBI web services provide programmatic access NCIBI data. Click on the tab above for instructions for using the particular service. Protein-protein interactions, pathways, compounds, literature, and genes merged from multiple sources. To use the web interface. Enriched for a particular gene. Enriched for a particular MeSH term. To use the web interface. Enriched for a particular compound.
Department of Computational Medicine and Bioinformatics. Assistant Professor of Computational Medicine and Bioinformatics, Medical School. Assistant Professor of Biostatistics, School of Public Health. Ann Arbor, MI 48109-2218. PhD, Biostatistics, University of Cincinnati, 2007. MS, Biomathematics, North Carolina State University, 2000. BS, Mathematics, minors in Biology and Computer science, Xavier University, 1998.
ChIP-Enrich tests ChIP-seq peak data for enrichment of biological pathways, Gene Ontology terms, and other types of gene sets. The pre-defined gene sets are the same as used in LRpath. And can be browsed here. ENCODE enrichment testing results can be accessed here. Number of peaks a gene must ha.
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We identified that lrpath.ncibi.org is weilding the Apache/2.4.6 (Red Hat Enterprise Linux) OpenSSL/1.0.2k-fips PHP/5.4.16 os.HTML TITLE
LRpath - Pathway Analysis using Logistic RegressionDESCRIPTION
Pathway Analysis using Logistic Regression. RNA-Enrich option for RNA-seq data. Why use our RNA-Enrich version? In tests for differential expression DE in RNA-seq data, there is often a relationship between gene read count and the statistical power to detect DE. This relationship has been shown to bias gene set enrichment testing. RNA-Enrich accounts for this bias empirically. Adjusting for read counts per gene improves the type 1 error rate and power of the test. The use of logistic regression. When L.PARSED CONTENT
The website states the following, "RNA-Enrich option for RNA-seq data." I analyzed that the web page stated " Why use our RNA-Enrich version? In tests for differential expression DE in RNA-seq data, there is often a relationship between gene read count and the statistical power to detect DE." They also stated " This relationship has been shown to bias gene set enrichment testing. RNA-Enrich accounts for this bias empirically. Adjusting for read counts per gene improves the type 1 error rate and power of the test. The use of logistic regression."ANALYZE OTHER WEB PAGES
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