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"title": "RNA-Seq - Princeton HTSEQ Users", "creators": [], "abstractNote": "Princeton High Throughput Sequencing Users Group", "websiteTitle": "", "websiteType": "", "date": "", "publisher": "", "place": "", "DOI": "", "citationKey": "", "url": "https://sites.google.com/site/princetonhtseq/tutorials/rna-seq", "accessDate": "2012-11-21T14:35:25Z", "shortTitle": "", "language": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "MAWHKN7K", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/MAWHKN7K", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/MAWHKN7K", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "MAWHKN7K", "version": 2, "itemType": "webpage", "title": "Gene Set Variation Package", "creators": [], "abstractNote": "", "websiteTitle": "", "websiteType": "", "date": "", "publisher": "", "place": "", "DOI": "", "citationKey": "", "url": "http://www.sagebase.org/research/gsva.php", "accessDate": "2012-11-28T08:55:14Z", "shortTitle": "", "language": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "CRF92VJ7", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/CRF92VJ7", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/CRF92VJ7", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "parsedDate": "2012", "numChildren": 0 }, "data": { "key": "CRF92VJ7", "version": 2, "itemType": "journalArticle", "title": "Detecting mutations in mixed sample sequencing data using empirical Bayes", "creators": [], "abstractNote": "", "publicationTitle": "The Annals of Applied Statistics", "publisher": "", "place": "", "date": "09/2012", "volume": "6", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "1047-1067", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1214/12-AOAS538", "citationKey": "", "url": "http://projecteuclid.org/euclid.aoas/1346418573", "accessDate": "2012-11-27T14:39:44Z", "PMID": "", "PMCID": "", "ISSN": "1932-6157", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "CrossRef", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "456N5JIP", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/456N5JIP", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/456N5JIP", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Young et al.", "parsedDate": "2010-02-04", "numChildren": 0 }, "data": { "key": "456N5JIP", "version": 2, "itemType": "journalArticle", "title": "Gene ontology analysis for RNA-seq: accounting for selection bias", "creators": [ { "creatorType": "author", "firstName": "Matthew", "lastName": "Young" }, { "creatorType": "author", "firstName": "Matthew", "lastName": "Wakefield" }, { "creatorType": "author", "firstName": "Gordon", "lastName": "Smyth" }, { "creatorType": "author", "firstName": "Alicia", "lastName": "Oshlack" } ], "abstractNote": "We present GOseq, an application for performing Gene Ontology (GO) analysis on RNA-seq data. GO analysis is widely used to reduce complexity and highlight biological processes in genome-wide expression studies, but standard methods give biased results on RNA-seq data due to over-detection of differential expression for long and highly expressed transcripts. Application of GOseq to a prostate cancer data set shows that GOseq dramatically changes the results, highlighting categories more consistent with the known biology.", "publicationTitle": "Genome Biology", "publisher": "", "place": "", "date": "2010-02-04", "volume": "11", "issue": "2", "section": "", "partNumber": "", "partTitle": "", "pages": "R14", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1186/gb-2010-11-2-r14", "citationKey": "", "url": "http://genomebiology.com/2010/11/2/R14/abstract", "accessDate": "2012-11-06T15:32:52Z", "PMID": "", "PMCID": "", "ISSN": "1465-6906", "archive": "", "archiveLocation": "", "shortTitle": "Gene ontology analysis for RNA-seq", "language": "en", "libraryCatalog": "genomebiology.com", "callNumber": "", "rights": "2010 Young et al.; licensee BioMed Central Ltd.", "extra": "", "tags": [ { "tag": "gene ontology" } ], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "J8NUEKC6", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/J8NUEKC6", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/J8NUEKC6", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "xu et al.", "parsedDate": "2012-08-24", "numChildren": 0 }, "data": { "key": "J8NUEKC6", "version": 2, "itemType": "journalArticle", "title": "Identification of miRNAs and their targets from Brassica napus by high-throughput sequencing and degradome analysis", "creators": [ { "creatorType": "author", "firstName": "miao yun", "lastName": "xu" }, { "creatorType": "author", "firstName": "yun", "lastName": "Dong" }, { "creatorType": "author", "firstName": "qiu xue", "lastName": "zhang" }, { "creatorType": "author", "firstName": "lan", "lastName": "zhang" }, { "creatorType": "author", "firstName": "yan zhong", "lastName": "luo" }, { "creatorType": "author", "firstName": "jie", "lastName": "sun" }, { "creatorType": "author", "firstName": "yun liu", "lastName": "fan" }, { "creatorType": "author", "firstName": "lei", "lastName": "wang" } ], "abstractNote": "MicroRNAs (miRNAs) are endogenous regulators of a broad range of physiological processes and act by either degrading mRNA or blocking its translation. Oilseed rape (Brassica napus) is one of the most important crops in China, Europe and other Asian countries with publicly available expressed sequence tags (ESTs) and genomic survey sequence (GSS) databases, but little is known about its miRNAs and their targets. To date, only 46 miRNAs have been identified in B. napus.", "publicationTitle": "BMC Genomics", "publisher": "", "place": "", "date": "2012-08-24", "volume": "13", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "421", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1186/1471-2164-13-421", "citationKey": "", "url": "http://www.biomedcentral.com/1471-2164/13/421/abstract", "accessDate": "2013-01-25T13:24:16Z", "PMID": "", "PMCID": "", "ISSN": "1471-2164", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.biomedcentral.com", "callNumber": "", "rights": "http://creativecommons.org/licenses/by/2.0/", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "I8B2V3UW", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/I8B2V3UW", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/I8B2V3UW", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Witten", "parsedDate": "2011-12", "numChildren": 0 }, "data": { "key": "I8B2V3UW", "version": 2, "itemType": "journalArticle", "title": "Classification and clustering of sequencing data using a Poisson model", "creators": [ { "creatorType": "author", "firstName": "Daniela M.", "lastName": "Witten" } ], "abstractNote": "In recent years, advances in high throughput sequencing technology have led to a need for specialized methods for the analysis of digital gene expression data. While gene expression data measured on a microarray take on continuous values and can be modeled using the normal distribution, RNA sequencing data involve nonnegative counts and are more appropriately modeled using a discrete count distribution, such as the Poisson or the negative binomial. Consequently, analytic tools that assume a Gaussian distribution (such as classification methods based on linear discriminant analysis and clustering methods that use Euclidean distance) may not perform as well for sequencing data as methods that are based upon a more appropriate distribution. Here, we propose new approaches for performing classification and clustering of observations on the basis of sequencing data. Using a Poisson log linear model, we develop an analog of diagonal linear discriminant analysis that is appropriate for sequencing data. We also propose an approach for clustering sequencing data using a new dissimilarity measure that is based upon the Poisson model. We demonstrate the performances of these approaches in a simulation study, on three publicly available RNA sequencing data sets, and on a publicly available chromatin immunoprecipitation sequencing data set.", "publicationTitle": "The Annals of Applied Statistics", "publisher": "", "place": "", "date": "2011-12", "volume": "5", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "2493-2518", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Ann. Appl. Stat.", "DOI": "10.1214/11-AOAS493", "citationKey": "", "url": "http://projecteuclid.org/euclid.aoas/1324399604", "accessDate": "2012-11-20T12:15:10Z", "PMID": "", "PMCID": "", "ISSN": "1932-6157", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "EN", "libraryCatalog": "Euclid", "callNumber": "", "rights": "", "extra": "Zentralblatt MATH identifier: 06017794; Mathematical Reviews number (MathSciNet): MR2907124", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "AJJQRPU2", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/AJJQRPU2", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/AJJQRPU2", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Wang et al.", "parsedDate": "2009-01-01", "numChildren": 0 }, "data": { "key": "AJJQRPU2", "version": 2, "itemType": "journalArticle", "title": "RNA-Seq: a revolutionary tool for transcriptomics", "creators": [ { "creatorType": "author", "firstName": "Zhong", "lastName": "Wang" }, { "creatorType": "author", "firstName": "Mark", "lastName": "Gerstein" }, { "creatorType": "author", "firstName": "Michael", "lastName": "Snyder" } ], "abstractNote": "RNA-Seq is a recently developed approach to transcriptome profiling that uses deep-sequencing technologies. Studies using this method have already altered our view of the extent and complexity of eukaryotic transcriptomes. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods. This article describes the RNA-Seq approach, the challenges associated with its application, and the advances made so far in characterizing several eukaryote transcriptomes.", "publicationTitle": "Nature Reviews Genetics", "publisher": "", "place": "", "date": "01/01/2009", "volume": "10", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "57-63", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1038/nrg2484", "citationKey": "", "url": "http://www.nature.com/nrg/journal/v10/n1/abs/nrg2484.html", "accessDate": "2012-11-20T12:13:37Z", "PMID": "", "PMCID": "", "ISSN": "1471-0056", "archive": "", "archiveLocation": "", "shortTitle": "RNA-Seq", "language": "en", "libraryCatalog": "www.nature.com", "callNumber": "", "rights": "© 2009 Nature Publishing Group", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "JJS29CAB", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/JJS29CAB", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/JJS29CAB", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Trapnell et al.", "parsedDate": "2010", "numChildren": 0 }, "data": { "key": "JJS29CAB", "version": 2, "itemType": "journalArticle", "title": "Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation", "creators": [ { "creatorType": "author", "firstName": "Cole", "lastName": "Trapnell" }, { "creatorType": "author", "firstName": "Brian A.", "lastName": "Williams" }, { "creatorType": "author", "firstName": "Geo", "lastName": "Pertea" }, { "creatorType": "author", "firstName": "Ali", "lastName": "Mortazavi" }, { "creatorType": "author", "firstName": "Gordon", "lastName": "Kwan" }, { "creatorType": "author", "firstName": "Marijke J. van", "lastName": "Baren" }, { "creatorType": "author", "firstName": "Steven L.", "lastName": "Salzberg" }, { "creatorType": "author", "firstName": "Barbara J.", "lastName": "Wold" }, { "creatorType": "author", "firstName": "Lior", "lastName": "Pachter" } ], "abstractNote": "High-throughput mRNA sequencing (RNA-Seq) promises simultaneous transcript discovery and abundance estimation. However, this would require algorithms that are not restricted by prior gene annotations and that account for alternative transcription and splicing. Here we introduce such algorithms in an open-source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed >430 million paired 75-bp RNA-Seq reads from a mouse myoblast cell line over a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Over the time series, 330 genes showed complete switches in the dominant transcription start site (TSS) or splice isoform, and we observed more subtle shifts in 1,304 other genes. These results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.", "publicationTitle": "Nature Biotechnology", "publisher": "", "place": "", "date": "2010", "volume": "28", "issue": "5", "section": "", "partNumber": "", "partTitle": "", "pages": "511-515", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1038/nbt.1621", "citationKey": "", "url": "http://www.nature.com/nbt/journal/v28/n5/full/nbt.1621.html", "accessDate": "2012-11-19T12:36:03Z", "PMID": "", "PMCID": "", "ISSN": "1087-0156", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.nature.com", "callNumber": "", "rights": "© 2010 Nature Publishing Group", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "5ERR72G6", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/5ERR72G6", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/5ERR72G6", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Trapnell et al.", "parsedDate": "2012", "numChildren": 0 }, "data": { "key": "5ERR72G6", "version": 2, "itemType": "journalArticle", "title": "Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks", "creators": [ { "creatorType": "author", "firstName": "Cole", "lastName": "Trapnell" }, { "creatorType": "author", "firstName": "Adam", "lastName": "Roberts" }, { "creatorType": "author", "firstName": "Loyal", "lastName": "Goff" }, { "creatorType": "author", "firstName": "Geo", "lastName": "Pertea" }, { "creatorType": "author", "firstName": "Daehwan", "lastName": "Kim" }, { "creatorType": "author", "firstName": "David R.", "lastName": "Kelley" }, { "creatorType": "author", "firstName": "Harold", "lastName": "Pimentel" }, { "creatorType": "author", "firstName": "Steven L.", "lastName": "Salzberg" }, { "creatorType": "author", "firstName": "John L.", "lastName": "Rinn" }, { "creatorType": "author", "firstName": "Lior", "lastName": "Pachter" } ], "abstractNote": "Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ~1 h of hands-on time.", "publicationTitle": "Nature Protocols", "publisher": "", "place": "", "date": "2012", "volume": "7", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "562-578", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1038/nprot.2012.016", "citationKey": "", "url": "http://www.nature.com/nprot/journal/v7/n3/full/nprot.2012.016.html", "accessDate": "2012-11-15T13:48:01Z", "PMID": "", "PMCID": "", "ISSN": "1754-2189", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.nature.com", "callNumber": "", "rights": "© 2012 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.", "extra": "", "tags": [ { "tag": "Computational Biology", "type": 1 }, { "tag": "Genomics", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "94IPXQI3", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/94IPXQI3", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/94IPXQI3", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Trapnell et al.", "parsedDate": "2009-05-01", "numChildren": 0 }, "data": { "key": "94IPXQI3", "version": 2, "itemType": "journalArticle", "title": "TopHat: discovering splice junctions with RNA-Seq", "creators": [ { "creatorType": "author", "firstName": "Cole", "lastName": "Trapnell" }, { "creatorType": "author", "firstName": "Lior", "lastName": "Pachter" }, { "creatorType": "author", "firstName": "Steven L.", "lastName": "Salzberg" } ], "abstractNote": "Motivation: A new protocol for sequencing the messenger RNA in a cell, known as RNA-Seq, generates millions of short sequence fragments in a single run. These fragments, or ‘reads’, can be used to measure levels of gene expression and to identify novel splice variants of genes. However, current software for aligning RNA-Seq data to a genome relies on known splice junctions and cannot identify novel ones. TopHat is an efficient read-mapping algorithm designed to align reads from an RNA-Seq experiment to a reference genome without relying on known splice sites.\nResults: We mapped the RNA-Seq reads from a recent mammalian RNA-Seq experiment and recovered more than 72% of the splice junctions reported by the annotation-based software from that study, along with nearly 20 000 previously unreported junctions. The TopHat pipeline is much faster than previous systems, mapping nearly 2.2 million reads per CPU hour, which is sufficient to process an entire RNA-Seq experiment in less than a day on a standard desktop computer. We describe several challenges unique to ab initio splice site discovery from RNA-Seq reads that will require further algorithm development.\nAvailability: TopHat is free, open-source software available from http://tophat.cbcb.umd.edu\nContact: cole@cs.umd.edu\nSupplementary information: Supplementary data are available at Bioinformatics online.", "publicationTitle": "Bioinformatics", "publisher": "", "place": "", "date": "05/01/2009", "volume": "25", "issue": "9", "section": "", "partNumber": "", "partTitle": "", "pages": "1105-1111", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Bioinformatics", "DOI": "10.1093/bioinformatics/btp120", "citationKey": "", "url": "http://bioinformatics.oxfordjournals.org/content/25/9/1105", "accessDate": "2012-11-15T14:06:38Z", "PMID": "", "PMCID": "", "ISSN": "1367-4803, 1460-2059", "archive": "", "archiveLocation": "", "shortTitle": "TopHat", "language": "en", "libraryCatalog": "bioinformatics.oxfordjournals.org", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "DZVM5RXM", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/DZVM5RXM", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/DZVM5RXM", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Toung et al.", "parsedDate": "2011-06-01", "numChildren": 0 }, "data": { "key": "DZVM5RXM", "version": 2, "itemType": "journalArticle", "title": "RNA-sequence analysis of human B-cells", "creators": [ { "creatorType": "author", "firstName": "Jonathan M.", "lastName": "Toung" }, { "creatorType": "author", "firstName": "Michael", "lastName": "Morley" }, { "creatorType": "author", "firstName": "Mingyao", "lastName": "Li" }, { "creatorType": "author", "firstName": "Vivian G.", "lastName": "Cheung" } ], "abstractNote": "RNA-sequencing (RNA-seq) allows quantitative measurement of expression levels of genes and their transcripts. In this study, we sequenced complementary DNA fragments of cultured human B-cells and obtained 879 million 50-bp reads comprising 44 Gb of sequence. The results allowed us to study the gene expression profile of B-cells and to determine experimental parameters for sequencing-based expression studies. We identified 20,766 genes and 67,453 of their alternatively spliced transcripts. More than 90% of the genes with multiple exons are alternatively spliced; for most genes, one isoform is predominantly expressed. We found that while chromosomes differ in gene density, the percentage of transcribed genes in each chromosome is less variable. In addition, genes involved in related biological processes are expressed at more similar levels than genes with different functions. Besides characterizing gene expression, we also used the data to investigate the effect of sequencing depth on gene expression measurements. While 100 million reads are sufficient to detect most expressed genes and transcripts, about 500 million reads are needed to measure accurately their expression levels. We provide examples in which deep sequencing is needed to determine the relative abundance of genes and their isoforms. With data from 20 individuals and about 40 million sequence reads per sample, we uncovered only 21 alternatively spliced, multi-exon genes that are not in databases; this result suggests that at this sequence coverage, we can detect most of the known genes. Results from this project are available on the UCSC Genome Browser to allow readers to study the expression and structure of genes in human B-cells.", "publicationTitle": "Genome Research", "publisher": "", "place": "", "date": "06/01/2011", "volume": "21", "issue": "6", "section": "", "partNumber": "", "partTitle": "", "pages": "991-998", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Genome Res.", "DOI": "10.1101/gr.116335.110", "citationKey": "", "url": "http://genome.cshlp.org/content/21/6/991", "accessDate": "2013-04-03T08:57:07Z", "PMID": "", "PMCID": "", "ISSN": "1088-9051, 1549-5469", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "genome.cshlp.org", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "3RIR6U8U", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/3RIR6U8U", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/3RIR6U8U", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Sun et al.", "parsedDate": "2012-12-30", "numChildren": 0 }, "data": { "key": "3RIR6U8U", "version": 2, "itemType": "journalArticle", "title": "Statistical Calibration of qRT-PCR, Microarray and RNA-Seq Gene Expression Data with Measurement Error Models", "creators": [ { "creatorType": "author", "firstName": "Zhaonan", "lastName": "Sun" }, { "creatorType": "author", "firstName": "Thomas", "lastName": "Kuczek" }, { "creatorType": "author", "firstName": "Yu", "lastName": "Zhu" } ], "abstractNote": "The accurate quantification of gene expression levels is crucial for transcriptome study. Microarray has been used as a main platform for simultaneously interrogating thousands of genes in the past decade, and recently RNA-Seq has emerged as a promising alternative. The gene expression measurements obtained by microarray and RNA-Seq are however subject to various measurement errors. A third platform called qRT-PCR is acknowledged to provide more accurate quantification of gene expression levels than microarray and RNA-Seq, but it has limited throughput capacity. In this article, we propose to use a system of functional measurement error models to model gene expression measurements and calibrate the microarray and RNA-Seq platforms with qRT-PCR. Based on the system, a two-step approach was developed to estimate the biases and error variance components of the three platforms and calculate calibrated estimates of gene expression levels. The estimated biases and variance components shed light on the relative strengths and weaknesses of the three platforms and the calibrated estimates provide a more accurate and consistent quantification of gene expression levels. Theoretical and simulation studies were conducted to establish the properties of those estimates. The system was applied to analyze two gene expression data from the Microarray Quality Control (MAQC) and Sequencing Quality Control (SEQC) projects.", "publicationTitle": "arXiv:1212.6690", "publisher": "", "place": "", "date": "2012-12-30", "volume": "", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "", "citationKey": "", "url": "http://arxiv.org/abs/1212.6690", "accessDate": "2013-01-07T14:05:05Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "arXiv.org", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Statistics - Applications", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "J64HANZP", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/J64HANZP", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/J64HANZP", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Storvall et al.", "parsedDate": "2013-01-18", "numChildren": 0 }, "data": { "key": "J64HANZP", "version": 2, "itemType": "journalArticle", "title": "Efficient and Comprehensive Representation of Uniqueness for Next-Generation Sequencing by Minimum Unique Length Analyses", "creators": [ { "creatorType": "author", "firstName": "Helena", "lastName": "Storvall" }, { "creatorType": "author", "firstName": "Daniel", "lastName": "Ramsköld" }, { "creatorType": "author", "firstName": "Rickard", "lastName": "Sandberg" } ], "abstractNote": "As next generation sequencing technologies are getting more efficient and less expensive, RNA-Seq is becoming a widely used technique for transcriptome studies. Computational analysis of RNA-Seq data often starts with the mapping of millions of short reads back to the genome or transcriptome, a process in which some reads are found to map equally well to multiple genomic locations (multimapping reads). We have developed the Minimum Unique Length Tool (MULTo), a framework for efficient and comprehensive representation of mappability information, through identification of the shortest possible length required for each genomic coordinate to become unique in the genome and transcriptome. Using the minimum unique length information, we have compared different uniqueness compensation approaches for transcript expression level quantification and demonstrate that the best compensation is achieved by discarding multimapping reads and correctly adjusting gene model lengths. We have also explored uniqueness within specific regions of the mouse genome and enhancer mapping experiments. Finally, by making MULTo available to the community we hope to facilitate the use of uniqueness compensation in RNA-Seq analysis and to eliminate the need to make additional mappability files.", "publicationTitle": "PLoS ONE", "publisher": "", "place": "", "date": "January 18, 2013", "volume": "8", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "e53822", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "PLoS ONE", "DOI": "10.1371/journal.pone.0053822", "citationKey": "", "url": "http://dx.doi.org/10.1371/journal.pone.0053822", "accessDate": "2013-02-05T15:01:41Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "PLoS ONE", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "HJH92C87", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/HJH92C87", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/HJH92C87", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Robinson et al.", "parsedDate": "2010-01-01", "numChildren": 1 }, "data": { "key": "HJH92C87", "version": 2, "itemType": "journalArticle", "title": "edgeR: a Bioconductor package for differential expression analysis of digital gene expression data", "creators": [ { "creatorType": "author", "firstName": "Mark D", "lastName": "Robinson" }, { "creatorType": "author", "firstName": "Davis J", "lastName": "McCarthy" }, { "creatorType": "author", "firstName": "Gordon K", "lastName": "Smyth" } ], "abstractNote": "SUMMARY: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. AVAILABILITY: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).", "publicationTitle": "Bioinformatics (Oxford, England)", "publisher": "", "place": "", "date": "Jan 1, 2010", "volume": "26", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "139-140", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Bioinformatics", "DOI": "10.1093/bioinformatics/btp616", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "1367-4811", "archive": "", "archiveLocation": "", "shortTitle": "edgeR", "language": "", "libraryCatalog": "NCBI PubMed", "callNumber": "", "rights": "", "extra": "PMID: 19910308", "tags": [ { "tag": "Algorithms", "type": 1 }, { "tag": "Gene Expression Profiling", "type": 1 }, { "tag": "Oligonucleotide Array Sequence Analysis", "type": 1 }, { "tag": "Programming Languages", "type": 1 }, { "tag": "Signal Processing, Computer-Assisted", "type": 1 }, { "tag": "Software", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "ZS63ZHP8", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/ZS63ZHP8", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/ZS63ZHP8", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Roberts et al.", "parsedDate": "2011-03-16", "numChildren": 0 }, "data": { "key": "ZS63ZHP8", "version": 2, "itemType": "journalArticle", "title": "Improving RNA-Seq expression estimates by correcting for fragment bias", "creators": [ { "creatorType": "author", "firstName": "Adam", "lastName": "Roberts" }, { "creatorType": "author", "firstName": "Cole", "lastName": "Trapnell" }, { "creatorType": "author", "firstName": "Julie", "lastName": "Donaghey" }, { "creatorType": "author", "firstName": "John", "lastName": "Rinn" }, { "creatorType": "author", "firstName": "Lior", "lastName": "Pachter" } ], "abstractNote": "The biochemistry of RNA-Seq library preparation results in cDNA fragments that are not uniformly distributed within the transcripts they represent. This non-uniformity must be accounted for when estimating expression levels, and we show how to perform the needed corrections using a likelihood based approach. We find improvements in expression estimates as measured by correlation with independently performed qRT-PCR and show that correction of bias leads to improved replicability of results across libraries and sequencing technologies.", "publicationTitle": "Genome Biology", "publisher": "", "place": "", "date": "2011-03-16", "volume": "12", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "R22", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1186/gb-2011-12-3-r22", "citationKey": "", "url": "http://genomebiology.com/2011/12/3/R22/abstract", "accessDate": "2012-11-19T12:35:33Z", "PMID": "", "PMCID": "", "ISSN": "1465-6906", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "genomebiology.com", "callNumber": "", "rights": "2011 Roberts et al.; licensee BioMed Central Ltd.", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "JK3XFTZ6", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/JK3XFTZ6", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/JK3XFTZ6", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Philippe et al.", "parsedDate": "2009-08-01", "numChildren": 0 }, "data": { "key": "JK3XFTZ6", "version": 2, "itemType": "journalArticle", "title": "Using reads to annotate the genome: influence of length, background distribution, and sequence errors on prediction capacity", "creators": [ { "creatorType": "author", "firstName": "Nicolas", "lastName": "Philippe" }, { "creatorType": "author", "firstName": "Anthony", "lastName": "Boureux" }, { "creatorType": "author", "firstName": "Laurent", "lastName": "Bréhélin" }, { "creatorType": "author", "firstName": "Jorma", "lastName": "Tarhio" }, { "creatorType": "author", "firstName": "Thérèse", "lastName": "Commes" }, { "creatorType": "author", "firstName": "Éric", "lastName": "Rivals" } ], "abstractNote": "Ultra high-throughput sequencing is used to analyse the transcriptome or interactome at unprecedented depth on a genome-wide scale. These techniques yield short sequence reads that are then mapped on a genome sequence to predict putatively transcribed or protein-interacting regions. We argue that factors such as background distribution, sequence errors, and read length impact on the prediction capacity of sequence census experiments. Here we suggest a computational approach to measure these factors and analyse their influence on both transcriptomic and epigenomic assays. This investigation provides new clues on both methodological and biological issues. For instance, by analysing chromatin immunoprecipitation read sets, we estimate that 4.6% of reads are affected by SNPs. We show that, although the nucleotide error probability is low, it significantly increases with the position in the sequence. Choosing a read length above 19 bp practically eliminates the risk of finding irrelevant positions, while above 20 bp the number of uniquely mapped reads decreases. With our procedure, we obtain 0.6% false positives among genomic locations. Hence, even rare signatures should identify biologically relevant regions, if they are mapped on the genome. This indicates that digital transcriptomics may help to characterize the wealth of yet undiscovered, low-abundance transcripts.", "publicationTitle": "Nucleic Acids Research", "publisher": "", "place": "", "date": "08/01/2009", "volume": "37", "issue": "15", "section": "", "partNumber": "", "partTitle": "", "pages": "e104-e104", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Nucl. Acids Res.", "DOI": "10.1093/nar/gkp492", "citationKey": "", "url": "http://nar.oxfordjournals.org/content/37/15/e104", "accessDate": "2013-04-03T11:11:01Z", "PMID": "", "PMCID": "", "ISSN": "0305-1048, 1362-4962", "archive": "", "archiveLocation": "", "shortTitle": "Using reads to annotate the genome", "language": "en", "libraryCatalog": "nar.oxfordjournals.org", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } }, { "key": "3CAFDJR3", "version": 2, "library": { "type": "group", "id": 161233, "name": "dernaseq", "links": { "alternate": { "href": "https://www.zotero.org/groups/dernaseq", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/161233/items/3CAFDJR3", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/dernaseq/items/3CAFDJR3", "type": "text/html" } }, "meta": { "createdByUser": { "id": 441886, "username": "joachim.jacob", "name": "Joachim Jacob", "links": { "alternate": { "href": "https://www.zotero.org/joachim.jacob", "type": "text/html" } } }, "creatorSummary": "Patrick et al.", "parsedDate": "2013-01-21", "numChildren": 0 }, "data": { "key": "3CAFDJR3", "version": 2, "itemType": "journalArticle", "title": "Improved moderation for gene-wise variance estimation in RNA-Seq via the exploitation of external information", "creators": [ { "creatorType": "author", "firstName": "Ellis", "lastName": "Patrick" }, { "creatorType": "author", "firstName": "Michael", "lastName": "Buckley" }, { "creatorType": "author", "firstName": "David M.", "lastName": "Lin" }, { "creatorType": "author", "firstName": "Yee H.", "lastName": "Yang" } ], "abstractNote": "The cost of RNA-Seq has been decreasing over the last few years. Despite this, experiments with four or less biological replicates are still quite common. Estimating the variances of gene expression estimates becomes both a challenging and interesting problem in these situations of low replication. However, with the wealth of microarray and other publicly available gene expression data readily accessible on public repositories, these sources of information can be leveraged to make improvements in variance estimation.", "publicationTitle": "BMC Genomics", "publisher": "", "place": "", "date": "2013-01-21", "volume": "14", "issue": "Suppl 1", "section": "", "partNumber": "", "partTitle": "", "pages": "S9", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1186/1471-2164-14-S1-S9", "citationKey": "", "url": "http://www.biomedcentral.com/1471-2164/14/S1/S9/abstract", "accessDate": "2013-02-15T09:04:12Z", "PMID": "", "PMCID": "", "ISSN": "1471-2164", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.biomedcentral.com", "callNumber": "", "rights": "2013 Patrick et al.; licensee BioMed Central Ltd.", "extra": "PMID: 23368783", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-04-15T11:51:54Z", "dateModified": "2013-04-15T11:51:54Z" } } ]