Alberto Risueño Pérez - Gredos - Universidad de Salamanca

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Risueño et al. BMC Bioinformatics 2010, 11:221 http://www.biomedcentral.com/1471-2105/11/221 or by GeneMapper); (7) total number of mouse genes assigned within the microarray; (8) percentage of significant genes with respect to the total. The highest ranked statistical value among the four comparisons is highlighted in yellow (although, it is important to note that the highest statistical rank does not imply the most biologically relevant change). In four out of five cases (IRS2, NRAS, SCD1 and ENG) the newly calculated gene mapping provides a better rank than the standard mapping, according to the statistical significance of the differential expression of the KO gene. The number of genes with q-value < 0.10 (which indicates the extension of the significant change) was the largest with the newly calculated gene mapping for two KO genes: APOE, 9.29% changed genes; NRAS, 0.28% changed genes. Finally, the p-value of the statistical test was lowest with the new mapping for KO genes ENG and IRS2. The results consistently indicate that the method using CDFs with the new remapping to "genes" provides at least as significant changes as the best of the three methods based on Affymetrix "probesets" CDFs. We emphasize that the purpose of these analyses is not to propose a new algorithm, but rather to determine in a comparative approach whether the array probe remappings provide results that are at least of equal quality to the original probesets. A complete evaluation of the methods will need a deep biological and functional analysis of the results that goes beyond the scope of this paper. To facilitate further analysis and independent comparison, we provide in the website the raw datasets (CEL files) corresponding to the results presented in Figure 3. More- Page 8 of 12 Figure 2 Table and pie graphs summarizing the probe mapping from four widely used human Affymetrix microarray models (U133A, U133 Plus 2.0, Gene 1.0 and Exon 1.0) to different transcribed entities. The figure includes information about the mapping and assignment of probes considering tree types: (i) green, probes mapped to translated genes (mRNAs, i.e. exons encoding for proteins); (ii) blue, probes mapped to ncRNAs (derived from RNAdb and from genes labeled as non-protein-coding in Ensembl); (iii) red, probes not mapped to any known RNA (NA, not assigned). over, APOE, NRAS and SCD1 microarray samples can be downloaded in GEO database: GSE2372, GSE14829 and GSE2926, respectively http://www.ncbi.nlm.nih.gov/geo. Remapping expression probes to ncRNAs As indicated above, the proportion of probes on the human arrays that map to genes was 78.9% for U133A, 52.9% for U133 Plus 2.0 and 25.5% for Exon 1.0. This efficiency is fractionally lower when only "protein-coding gene loci" (i.e. loci that encode mRNAs translated to proteins) are considered: 78.0% for U133A, 52.3% for U133 Plus 2.0 and 23.8% for Exon 1.0 arrays. This shows that a large fraction of probes within these microarrays do not map to any known protein-coding RNA (i.e. mRNA). Therefore, we performed a remapping of those probes not assigned to mRNAs to a database of ncRNA sequences (RNAdb v.1 from 2009) [4]. These ncRNAs belong to the mRNA-like class of long ncRNAs. These were predominantly identified in cDNA libraries, such as those used in the FANTOM3 and H-Invitational datasets [1,16]. Because cDNA library generation typically involves poly-dT priming, such cDNA sequences largely arise from polyadenylated transcripts. However, due to the possibility of internal priming from polyA-rich tracts, some non-polyadenylated transcripts may also be present. Nevertheless, such transcripts are represented in any gene expression study that employs a microarray protocol that selectively amplifies polyadenylated transcripts by poly-dT priming. The new generation Affymetrix microarrays Gene 1.0 and Exon 1.0 use WT random primed amplification, which does not necessitate the
Risueño et al. BMC Bioinformatics 2010, 11:221 http://www.biomedcentral.com/1471-2105/11/221 presence of a poly-A tail. This type of microarrays can detect many more ncRNAs. The results of the remapping of array probes to ncR- NAs showed that 29.7% of the probes from human Exon 1.0 and 26.5% of the probes from U133 Plus 2.0 map to Page 9 of 12 Figure 3 Comparison of the differential expression calculated by the SAM algorithm for a series of data of mouse microarrays (five sets of six samples) analyzed using three different expression signal calculation algorithms (MAS5.0, FARMS and RMA) with standard CDFs to "probesets" or using RMA with CDFs to "genes" (GeneMapper CDFs). Each set includes three biological replicates of knock-out (KO) mice for a specific gene compared to three replicates of the corresponding wild-type (WT) mice. The gene KOs are: APOE-/-, IRS2-/-, NRAS-/-, SCD1-/- and ENG+/ -. The full name of these genes, the Ensembl ID number (ENSG) and the probesets assigned by Affymetrix are indicated in the top line of each set, labelled Entry (1). The table shows the numbers for the statistical parameters calculated in the comparison, which are: (2) rank of the KO gene across down-regulated genes; (3) rank of the KO gene across all genes; (4) p-value from SAM for the KO gene; (5) d-value from SAM for the KO gene; (6) number of significant gene loci with q-value < 0.10 (this calculation was performed such that all probesets were assigned to specific genes following the Affymetrix assignment or the GeneMapper assignment; therefore the methods are comparable since the number of gene loci indicated are the fraction of total mouse genes assigned); (7) total number of mouse gene loci assigned within the microarray; (8) percentage of significant gene loci with respect to the total. Yellow background indicates the top values for each statistical parameter calculated with each of the four procedures used. The comparison that includes the identical methods for expression calculation (RMA) and for differential expression (SAM) changing only the CDFs is presented in the last two columns, framed with a black line. ncRNAs. A summary of this remapping is presented in Figure 2, which shows the percentages of probes that map to ncRNAs, combining both the information from RNAdb and from genes labeled as non-protein-coding in
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Bioinformática aplicada a estudios
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Índice INTRODUCCIÓN GENERAL .....
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Introducción general Bioinformáti
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Figura 2. Proceso de transcripción
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Introducción general caciones, las
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Objetivos Introducción general La
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Capítulo 1 Paso 2 Descripción: As
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Capítulo 1 Para optimizar la preci
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Figura 1.9a. Distribución del núm
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Capítulo 1 por contraste el númer
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Capítulo 1 (cromosoma, locus, exon
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Capítulo 1 su presentación y deta
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Tesis Doctoral los genes encontrado
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Tesis Doctoral real (RT-‐PCR).
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Page 133 and 134: ORIGINAL ARTICLE Deregulation of mi
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