01929nas a2200253   4500008004100000022001400041245006800055210006500123260001600188300001100204490000700215520118200222653000801404100003001412700002901442700002101471700001801492700001801510700002001528700002101548700002101569700001601590856006901606       2012                        eng d  a1367-481100aQualimap: evaluating next-generation sequencing alignment data.0 aQualimap evaluating nextgeneration sequencing alignment data  c2012 Oct 15  a2678-90 v283 aMOTIVATION: The sequence alignment/map (SAM) and the binary alignment/map (BAM) formats have become the standard method of representation of nucleotide sequence alignments for next-generation sequencing data. SAM/BAM files usually contain information from tens to hundreds of millions of reads. Often, the sequencing technology, protocol and/or the selected mapping algorithm introduce some unwanted biases in these data. The systematic detection of such biases is a non-trivial task that is crucial to drive appropriate downstream analyses. RESULTS: We have developed Qualimap, a Java application that supports user-friendly quality control of mapping data, by considering sequence features and their genomic properties. Qualimap takes sequence alignment data and provides graphical and statistical analyses for the evaluation of data. Such quality-control data are vital for highlighting problems in the sequencing and/or mapping processes, which must be addressed prior to further analyses. AVAILABILITY: Qualimap is freely available from http://www.qualimap.org. CONTACT: aconesa@cipf.es SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.10aNGS1 aGarcía-Alcalde, Fernando1 aOkonechnikov, Konstantin1 aCarbonell, José1 aCruz, Luis, M1 aGötz, Stefan1 aTarazona, Sonia1 aDopazo, Joaquín1 aMeyer, Thomas, F1 aConesa, Ana  uhttp://bioinformatics.oxfordjournals.org/content/28/20/2678.long02754nas a2200217   4500008004100000022001400041245012800055210006900183260000900252300000700261490000600268520203200274100002702306700003302333700003002366700002902396700002002425700001602445700001802461856005702479       2012                        eng d  a2193-180100aTransdifferentiation of MALME-3M and MCF-7 Cells toward Adipocyte-like Cells is Dependent on Clathrin-mediated Endocytosis.0 aTransdifferentiation of MALME3M and MCF7 Cells toward Adipocytel  c2012  a440 v13 aABSTRACT: Enforced cell transdifferentiation of human cancer cells is a promising alternative to conventional chemotherapy. We previously identified albumin-associated lipid- and, more specifically, saturated fatty acid-induced transdifferentiation programs in human cancer cells (HCCLs). In this study, we further characterized the adipocyte-like cells, resulting from the transdifferentiation of human cancer cell lines MCF-7 and MALME-3M, and proposed a common mechanistic approach for these transdifferentiating programs. We showed the loss of pigmentation in MALME-3M cells treated with albumin-associated lipids, based on electron microscopic analysis, and the overexpression of perilipin 2 (PLIN2) by western blotting in MALME-3M and MCF-7 cells treated with unsaturated fatty acids. Comparing the gene expression profiles of naive melanoma MALME-3M cells and albumin-associated lipid-treated cells, based on RNA sequencing, we confirmed the transcriptional upregulation of some key adipogenic gene markers and also an alternative splicing of the adipogenic master regulator PPARG, that is probably related to the reported up regulated expression of the protein. Most importantly, these results also showed the upregulation of genes responsible for Clathrin (CLTC) and other adaptor-related proteins. An increase in CLTC expression in the transdifferentiated cells was confirmed by western blotting. Inactivation of CLTC by chlorpromazine (CHP), an inhibitor of CTLC mediated endocytosis (CME), and gene silencing by siRNAs, partially reversed the accumulation of neutral lipids observed in the transdifferentiated cells. These findings give a deeper insight into the phenotypic changes observed in HCCL to adipocyte-like transdifferentiation and point towards CME as a key pathway in distinct transdifferentiation programs. DISCLOSURES: Simon C and Aguilar-Gallardo C are co-inventors of the International Patent Application No. PCT/EP2011/004941 entitled "Methods for tumor treatment and adipogenesis differentiation".1 aCarcel-Trullols, Jaime1 aAguilar-Gallardo, Cristóbal1 aGarcía-Alcalde, Fernando1 aPardo-Cea, Miguel, Angel1 aDopazo, Joaquin1 aConesa, Ana1 aSimon, Carlos  uhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3725915/02499nas a2200277   4500008004100000022001400041245005900055210005600114260001300170300001200183490000700195520165100202653001501853653002801868653003001896653003101926653001101957653002001968653004401988100002002032700003002052700002002082700002002102700001602122856008302138       2011                        eng d  a1549-546900aDifferential expression in RNA-seq: a matter of depth.0 aDifferential expression in RNAseq a matter of depth  c2011 Dec  a2213-230 v213 a<p>Next-generation sequencing (NGS) technologies are revolutionizing genome research, and in particular, their application to transcriptomics (RNA-seq) is increasingly being used for gene expression profiling as a replacement for microarrays. However, the properties of RNA-seq data have not been yet fully established, and additional research is needed for understanding how these data respond to differential expression analysis. In this work, we set out to gain insights into the characteristics of RNA-seq data analysis by studying an important parameter of this technology: the sequencing depth. We have analyzed how sequencing depth affects the detection of transcripts and their identification as differentially expressed, looking at aspects such as transcript biotype, length, expression level, and fold-change. We have evaluated different algorithms available for the analysis of RNA-seq and proposed a novel approach--NOISeq--that differs from existing methods in that it is data-adaptive and nonparametric. Our results reveal that most existing methodologies suffer from a strong dependency on sequencing depth for their differential expression calls and that this results in a considerable number of false positives that increases as the number of reads grows. In contrast, our proposed method models the noise distribution from the actual data, can therefore better adapt to the size of the data set, and is more effective in controlling the rate of false discoveries. This work discusses the true potential of RNA-seq for studying regulation at low expression ranges, the noise within RNA-seq data, and the issue of replication.</p>10aAlgorithms10aExpressed Sequence Tags10aGene Expression Profiling10aGene Expression Regulation10aHumans10aModels, Genetic10aOligonucleotide Array Sequence Analysis1 aTarazona, Sonia1 aGarcía-Alcalde, Fernando1 aDopazo, Joaquin1 aFerrer, Alberto1 aConesa, Ana  uhttp://clinbioinfosspa.es/content/differential-expression-rna-seq-matter-depth01129nas a2200169   4500008004100000245010300041210006900144260001500213300001000228490000700238520049600245100003000741700002900771700002100800700001600821856012200837       2011                        eng d00aPaintomics: a web based tool for the joint visualization of transcriptomics and metabolomics data.0 aPaintomics a web based tool for the joint visualization of trans  c2011 Jan 1  a137-90 v273 a<p>The development of the omics technologies such as transcriptomics, proteomics and metabolomics has made possible the realization of systems biology studies where biological systems are interrogated at different levels of biochemical activity (gene expression, protein activity and/or metabolite concentration). An effective approach to the analysis of these complex datasets is the joined visualization of the disparate biomolecular data on the framework of known biological pathways.</p>1 aGarcía-Alcalde, Fernando1 aGarcía-López, Federico1 aDopazo, Joaquín1 aConesa, Ana  uhttp://clinbioinfosspa.es/content/paintomics-web-based-tool-joint-visualization-transcriptomics-and-metabolomics-data