Received:\u00a04 June 2010<\/p>\n
Accepted:\u00a016 November 2010<\/p>\n
Published:\u00a016 November 2010<\/p>\n
\u00a9 2010 Wu et al; licensee BioMed Central Ltd.<\/p>\n
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http:\/\/creativecommons.org\/licenses\/by\/2.0<\/a>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.<\/p>\n Abstract<\/p>\n Background<\/p>\n Recent technological advancements have made high throughput sequencing an increasingly popular approach for transcriptome analysis. Advantages of sequencing-based transcriptional profiling over microarrays have been reported, including lower technical variability. However, advances in technology do not remove biological variation between replicates and this variation is often neglected in many analyses.<\/p>\n Results<\/p>\n We propose an empirical Bayes method, titled Analysis of Sequence Counts (ASC), to detect differential expression based on sequencing technology. ASC borrows information across sequences to establish prior distribution of sample variation, so that biological variation can be accounted for even when replicates are not available. Compared to current approaches that simply tests for equality of proportions in two samples, ASC is less biased towards highly expressed sequences and can identify more genes with a greater log fold change at lower overall abundance.<\/p>\n Conclusions<\/p>\n ASC unifies the biological and statistical significance of differential expression by estimating the posterior mean of log fold change and estimating false discovery rates based on the posterior mean. The implementation in R is available at\u00a0http:\/\/www.stat.brown.edu\/Zwu\/research.aspx<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" Received:\u00a04 June 2010 Accepted:\u00a016 November 2010 Published:\u00a016 November 2010 \u00a9 2010 Wu et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http:\/\/creativecommons.org\/licenses\/by\/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background Recent […]<\/p>\n","protected":false},"author":581,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[21],"tags":[],"class_list":["post-381","post","type-post","status-publish","format-standard","hentry","category-news"],"acf":[],"_links":{"self":[{"href":"https:\/\/web.uri.edu\/rinsfepscor\/wp-json\/wp\/v2\/posts\/381","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.uri.edu\/rinsfepscor\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/web.uri.edu\/rinsfepscor\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/rinsfepscor\/wp-json\/wp\/v2\/users\/581"}],"replies":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/rinsfepscor\/wp-json\/wp\/v2\/comments?post=381"}],"version-history":[{"count":0,"href":"https:\/\/web.uri.edu\/rinsfepscor\/wp-json\/wp\/v2\/posts\/381\/revisions"}],"wp:attachment":[{"href":"https:\/\/web.uri.edu\/rinsfepscor\/wp-json\/wp\/v2\/media?parent=381"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/web.uri.edu\/rinsfepscor\/wp-json\/wp\/v2\/categories?post=381"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/web.uri.edu\/rinsfepscor\/wp-json\/wp\/v2\/tags?post=381"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}