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2. Relative power and sample size analysis on gene expression profiling data

Author

den Dunnen JT, Hooiveld GJEJ, Pedotti P, 't Hoen PAC, van Iterson M, van Ommen GJB, Boer JM, and Menezes RX

Subjects
Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background With the increasing number of expression profiling technologies, researchers today are confronted with choosing the technology that has sufficient power with minimal sample size, in order to reduce cost and time. These depend on data variability, partly determined by sample type, preparation and processing. Objective measures that help experimental design, given own pilot data, are thus fundamental. Results Relative power and sample size analysis were performed on two distinct data sets. The first set consisted of Affymetrix array data derived from a nutrigenomics experiment in which weak, intermediate and strong PPARα agonists were administered to wild-type and PPARα-null mice. Our analysis confirms the hierarchy of PPARα-activating compounds previously reported and the general idea that larger effect sizes positively contribute to the average power of the experiment. A simulation experiment was performed that mimicked the effect sizes seen in the first data set. The relative power was predicted but the estimates were slightly conservative. The second, more challenging, data set describes a microarray platform comparison study using hippocampal δC-doublecortin-like kinase transgenic mice that were compared to wild-type mice, which was combined with results from Solexa/Illumina deep sequencing runs. As expected, the choice of technology greatly influences the performance of the experiment. Solexa/Illumina deep sequencing has the highest overall power followed by the microarray platforms Agilent and Affymetrix. Interestingly, Solexa/Illumina deep sequencing displays comparable power across all intensity ranges, in contrast with microarray platforms that have decreased power in the low intensity range due to background noise. This means that deep sequencing technology is especially more powerful in detecting differences in the low intensity range, compared to microarray platforms. Conclusion Power and sample size analysis based on pilot data give valuable information on the performance of the experiment and can thereby guide further decisions on experimental design. Solexa/Illumina deep sequencing is the technology of choice if interest lies in genes expressed in the low-intensity range. Researchers can get guidance on experimental design using our approach on their own pilot data implemented as a BioConductor package, SSPA http://bioconductor.org/packages/release/bioc/html/SSPA.html.

Published
2009
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3. WGS-based telomere length analysis in Dutch family trios implicates stronger maternal inheritance and a role for RRM1 gene

Author

Nersisyan, L, Nikoghosyan, M, Francioli, LC, Menelaou, A, Pulit, SL, Elbers, CC, Leeuwen, Elisa, Karssen, Lennart, Amin, Najaf, Rivadeneira, Fernando, Isaacs, Aaron, Hofman, Bert, Uitterlinden, André, Duijn, Cornelia, Oven, Mannis, Kayser, Manfred, Estrada Gil, Karol, Koval, Slavik, Medina Gomez, Maria, Oostra, Ben, van Ommen, GJB, Arakelyan, A, Nersisyan, L, Nikoghosyan, M, Francioli, LC, Menelaou, A, Pulit, SL, Elbers, CC, Leeuwen, Elisa, Karssen, Lennart, Amin, Najaf, Rivadeneira, Fernando, Isaacs, Aaron, Hofman, Bert, Uitterlinden, André, Duijn, Cornelia, Oven, Mannis, Kayser, Manfred, Estrada Gil, Karol, Koval, Slavik, Medina Gomez, Maria, Oostra, Ben, van Ommen, GJB, and Arakelyan, A

Published
2019

4. Search for Early Pancreatic Cancer Blood Biomarkers in Five European Prospective Population Biobanks Using Metabolomics

Author

Fest, J (Jesse), Vijfhuizen, LS, Goeman, JJ, Veth, O, Joensuu, A, Perola, M, Mannisto, S, Ness-Jensen, E, Hveem, K, Haller, T, Tonisson, N, Mikkel, K, Metspalu, A, Duijn, Cornelia, Ikram, A (Aqsa), Stricker, Bruno, Ruiter, Roel, van Eijck, Casper, van Ommen, GJB, 't Hoen, PAC, Fest, J (Jesse), Vijfhuizen, LS, Goeman, JJ, Veth, O, Joensuu, A, Perola, M, Mannisto, S, Ness-Jensen, E, Hveem, K, Haller, T, Tonisson, N, Mikkel, K, Metspalu, A, Duijn, Cornelia, Ikram, A (Aqsa), Stricker, Bruno, Ruiter, Roel, van Eijck, Casper, van Ommen, GJB, and 't Hoen, PAC

Published
2019

6. Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

Author

Van Leeuwen, EM, Karssen, LC, Deelen, J, Isaacs, A, Medina-Gomez, C, Mbarek, H, Kanterakis, A, Trompet, S, Postmus, I, Verweij, N, Van Enckevort, DJ, Huffman, JE, White, CC, Feitosa, MF, Bartz, TM, Manichaikul, A, Joshi, PK, Peloso, GM, Deelen, P, Van Dijk, F, Willemsen, G, De Geus, EJ, Milaneschi, Y, Penninx, BWJH, Francioli, LC, Menelaou, A, Pulit, SL, Rivadeneira, F, Hofman, A, Oostra, BA, Franco, OH, Leach, IM, Beekman, M, De Craen, AJM, Uh, HW, Trochet, H, Hocking, LJ, Porteous, DJ, Sattar, N, Packard, CJ, Buckley, BM, Brody, JA, Bis, JC, Rotter, JI, Mychaleckyj, JC, Campbell, H, Duan, Q, Lange, LA, Wilson, JF, Hayward, C, Polasek, O, Vitart, V, Rudan, I, Wright, AF, Rich, SS, Psaty, BM, Borecki, IB, Kearney, PM, Stott, DJ, Cupples, LA, Jukema, JW, Van Der Harst, P, Sijbrands, EJ, Hottenga, JJ, Uitterlinden, AG, Swertz, MA, Van Ommen, GJB, De Bakker, PIW, Eline Slagboom, P, Boomsma, DI, Wijmenga, C, Van Duijn, CM, Neerincx, PBT, Elbers, CC, Palamara, PF, Peer, I, Abdellaoui, A, Kloosterman, WP, Van Oven, M, Vermaat, M, Li, M, Laros, JFJ, Stoneking, M, De Knijff, P, Kayser, M, Veldink, JH, Van Den Berg, LH, Byelas, H, Den Dunnen, JT, Dijkstra, M, Amin, N, Van Der Velde, KJ, and Van Setten, J

Abstract

© 2015 Macmillan Publishers Limited. All rights reserved. Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (∼35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value

Published
2015
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7. The Implicitome: A Resource for Rationalizing Gene-Disease Associations

Author

Hettne, KM, Thompson, M, van Haagen, HHHBM, van der Horst, E, Kaliyaperumal, R, Mina, E, Tatum, Z, Laros, JFJ, van Mulligen, Erik, Schuemie, Martijn, Aten, E, Li, T S, Bruskiewich, R, Good, B M, Su, A I, Kors, Jan, den Dunnen, J, van Ommen, GJB, Roos, M, 't Hoen, PA, Mons, B, Schultes, E A, Hettne, KM, Thompson, M, van Haagen, HHHBM, van der Horst, E, Kaliyaperumal, R, Mina, E, Tatum, Z, Laros, JFJ, van Mulligen, Erik, Schuemie, Martijn, Aten, E, Li, T S, Bruskiewich, R, Good, B M, Su, A I, Kors, Jan, den Dunnen, J, van Ommen, GJB, Roos, M, 't Hoen, PA, Mons, B, and Schultes, E A

Published
2016

9. Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

Author

Leeuwen, Elisa, Karssen, Lennart, Deelen, J, Isaacs, Aaron, Medina-Gomez, C, Mbarek, H, Kanterakis, A, Trompet, S, Postmus, I, Verweij, N (Niek), van Enckevort, DJ, Huffman, JE, White, CC, Feitosa, MF, Bartz, TM, Manichaikul, A, Joshi, PK, Peloso, GM, Deelen, P, Dijk, Femke, Willemsen, G, de Geus, EJ, Milaneschi, Y, Penninx, BWJH, Francioli, LC, Menelaou, A, Pulit, SL, Rivadeneira, Fernando, Hofman, Bert, Oostra, Ben, Franco Duran, OH, Leach, IM, Beekman, M, de Craen, AJM, Uh, HW, Trochet, H, Hocking, LJ, Porteous, DJ, Sattar, N, Packard, CJ, Buckley, BM, Brody, JA, Bis, JC, Rotter, JI, Mychaleckyj, JC, Campbell, H, Duan, Q, Lange, LA, Wilson, JF, Hayward, C, Polasek, O, Vitart, V, Rudan, I, Wright, AF, Rich, SS, Psaty, BM, Borecki, IB, Kearney, PM, Stott, DJ, Cupples, LA, Jukema, JW, van der Harst, P, Sijbrands, E.J.G., Hottenga, JJ (Jouke Jan), Uitterlinden, André, Swertz, MA, van Ommen, GJB, de Bakker, PIW, Slagboom, PE (Eline), Boomsma, DI, Wijmenga, C, Duijn, Cornelia, Leeuwen, Elisa, Karssen, Lennart, Deelen, J, Isaacs, Aaron, Medina-Gomez, C, Mbarek, H, Kanterakis, A, Trompet, S, Postmus, I, Verweij, N (Niek), van Enckevort, DJ, Huffman, JE, White, CC, Feitosa, MF, Bartz, TM, Manichaikul, A, Joshi, PK, Peloso, GM, Deelen, P, Dijk, Femke, Willemsen, G, de Geus, EJ, Milaneschi, Y, Penninx, BWJH, Francioli, LC, Menelaou, A, Pulit, SL, Rivadeneira, Fernando, Hofman, Bert, Oostra, Ben, Franco Duran, OH, Leach, IM, Beekman, M, de Craen, AJM, Uh, HW, Trochet, H, Hocking, LJ, Porteous, DJ, Sattar, N, Packard, CJ, Buckley, BM, Brody, JA, Bis, JC, Rotter, JI, Mychaleckyj, JC, Campbell, H, Duan, Q, Lange, LA, Wilson, JF, Hayward, C, Polasek, O, Vitart, V, Rudan, I, Wright, AF, Rich, SS, Psaty, BM, Borecki, IB, Kearney, PM, Stott, DJ, Cupples, LA, Jukema, JW, van der Harst, P, Sijbrands, E.J.G., Hottenga, JJ (Jouke Jan), Uitterlinden, André, Swertz, MA, van Ommen, GJB, de Bakker, PIW, Slagboom, PE (Eline), Boomsma, DI, Wijmenga, C, and Duijn, Cornelia

Abstract

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (similar to 35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value < 6.61 x 10(-4)), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (beta(LDL-C) = 0.135, beta(TC) = 0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.

Published
2015

11. Novel Protein-Protein Interactions Inferred from Literature Context

Author

Haagen, Herman, 't Hoen, PAC, Bovo, AB, de Morree, A, van Mulligen, Erik, Chichester, C, Kors, Jan, Dunnen, JT, van Ommen, GJB, van der Maarel, SM, Kern, VM, Mons, B, Schuemie, Martijn, Haagen, Herman, 't Hoen, PAC, Bovo, AB, de Morree, A, van Mulligen, Erik, Chichester, C, Kors, Jan, Dunnen, JT, van Ommen, GJB, van der Maarel, SM, Kern, VM, Mons, B, and Schuemie, Martijn

Abstract

We have developed a method that predicts Protein-Protein Interactions (PPIs) based on the similarity of the context in which proteins appear in literature. This method outperforms previously developed PPI prediction algorithms that rely on the conjunction of two protein names in MEDLINE abstracts. We show significant increases in coverage (76% versus 32%) and sensitivity (66% versus 41% at a specificity of 95%) for the prediction of PPIs currently archived in 6 PPI databases. A retrospective analysis shows that PPIs can efficiently be predicted before they enter PPI databases and before their interaction is explicitly described in the literature. The practical value of the method for discovery of novel PPIs is illustrated by the experimental confirmation of the inferred physical interaction between CAPN3 and PARVB, which was based on frequent co-occurrence of both proteins with concepts like Z-disc, dysferlin, and alpha-actinin. The relationships between proteins predicted by our method are broader than PPIs, and include proteins in the same complex or pathway. Dependent on the type of relationships deemed useful, the precision of our method can be as high as 90%. The full set of predicted interactions is available in a downloadable matrix and through the webtool Nermal, which lists the most likely interaction partners for a given protein. Our framework can be used for prioritizing potential interaction partners, hitherto undiscovered, for follow-up studies and to aid the generation of accurate protein interaction maps.

Published
2009

12. Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease

Author

Jelier, R (Rob), 't Hoen, PAC, Sterrenburg, E, Dunnen, JT, van Ommen, GJB, Kors, Jan, Mons, B, Jelier, R (Rob), 't Hoen, PAC, Sterrenburg, E, Dunnen, JT, van Ommen, GJB, Kors, Jan, and Mons, B

Abstract

Background: Comparative analysis of expression microarray studies is difficult due to the large influence of technical factors on experimental outcome. Still, the identified differentially expressed genes may hint at the same biological processes. However, manually curated assignment of genes to biological processes, such as pursued by the Gene Ontology (GO) consortium, is incomplete and limited. We hypothesised that automatic association of genes with biological processes through thesaurus-controlled mining of Medline abstracts would be more effective. Therefore, we developed a novel algorithm (LAMA: Literature-Aided Meta-Analysis) to quantify the similarity between transcriptomics studies. We evaluated our algorithm on a large compendium of 102 microarray studies published in the field of muscle development and disease, and compared it to similarity measures based on gene overlap and over-representation of biological processes assigned by GO. Results: While the overlap in both genes and overrepresented GO-terms was poor, LAMA retrieved many more biologically meaningful links between studies, with substantially lower influence of technical factors. LAMA correctly grouped muscular dystrophy, regeneration and myositis studies, and linked patient and corresponding mouse model studies. LAMA also retrieves the connecting biological concepts. Among other new discoveries, we associated cullin proteins, a class of ubiquitinylation proteins, with genes down-regulated during muscle regeneration, whereas ubiquitinylation was previously reported to be activated during the inverse process: muscle atrophy. Conclusion: Our literature-based association analysis is capable of finding hidden common biological denominators in microarray studies, and circumvents the need for raw data analysis or curated gene annotation databases.

Published
2008

13. Two-colour immunocytochemical staining of gamma (gamma) and epsilon (epsilon) type haemoglobin in fetal red cells

Author

Mesker, WE, Velzen, MCMOV, Oosterwijk, JC, Bernini, LF, Golbus, MS, Kanhai, HHH, Van Ommen, GJB, Tanke, HJ, Damage and Repair in Cancer Development and Cancer Treatment (DARE), and Targeted Gynaecologic Oncology (TARGON)

Subjects
immunocytochemistry, prenatal diagnosis, MONOCLONAL-ANTIBODY, embryonic haemoglobin, ERYTHROBLASTS, hemic and lymphatic diseases, fetal haemoglobin, GLOBIN CHAINS, monoclonal antibodies, ENRICHMENT, MATERNAL BLOOD, IMMUNOASSAY
Abstract

We have developed a two-colour immunocytochemical staining method for the detection of fetal and embryonic haemoglobin in erythroid cells. The method was applied to study these haemoglobin types in fetal red cells. Specimens from fetal blood (10 weeks), cord blood and fetal liver (14 weeks) as well as chorionic villus samples (10-13 weeks) were stained for gamma and epsilon chains using CY3 and FITC labelled antibodies. Morphometric analysis was applied to determine cell size. Samples from organs involved in early embryonic development contained relatively large erythroblasts expressing the epsilon globin chain (megaloblasts); later in gestation the gamma chain was co-expressed by the same cells which ultimately became smaller and contained HbF (alpha(2)gamma(2)) only. This phenomenon was confirmed in CVS samples in which all cell types were abundantly present. Since fetal erythroblasts are considered candidate cells for non-invasive prenatal diagnosis using FISH, we studied the phenotype of erythroblasts circulating in the maternal blood. The majority of erythroblasts in maternal blood appeared to be of the relatively small gamma globin-containing cell type. However, careful screening of the same maternal blood samples also revealed erythroblasts expressing epsilon or epsilon and gamma globins simultaneously, although at low frequency. Control specimens from non-pregnant women did not show nucleated red cells expressing either of the haemoglobin types. These observations may contribute to the better recognition of fetal cells in the maternal blood for prenatal diagnosis. (C) 1998 John Wiley & Sons, Ltd.

Published
1998

14. Fetal cell detection in maternal blood: A study in 236 samples using erythroblast morphology, DAB and HbF staining, and FISH analysis

Author

Oosterwijk, JC, Mesker, WE, Ouwerkerk-van Velzen, MCM, Knepfle, CFHM, Wiesmeijer, KC, Beverstock, GC, van Ommen, GJB, Kanhai, HHH, Tanke, HJ, Damage and Repair in Cancer Development and Cancer Treatment (DARE), and Targeted Gynaecologic Oncology (TARGON)

Subjects
fetal hemoglobin, chorionic villus sampling, prenatal diagnosis, hemoglobin gamma-chain, FLOW-CYTOMETRY, POLYMERASE CHAIN-REACTION, IN-SITU HYBRIDIZATION, PERIPHERAL-BLOOD, DIAGNOSIS, 3,3-diaminobenzidin, TROPHOBLAST, immunocytochemistry, FISH, rare event detection, PRENATAL SEX DETERMINATION, nucleated red blood cell, NUCLEATED ERYTHROCYTES, fetal-maternal transfusion, ENRICHMENT, PREGNANT-WOMEN
Abstract

A protocol to detect fetal nucleated red blood cells (NRBCs) was tested in 217 pregnant women and in 19 nonpregnant controls. All the pregnant women were sampled after chorionic villus sampling (CVS); 20 were also sampled pre-CVS. NRBC recognition was based upon morphology by using staining of hemoglobin with 3,3-diaminobenzidin (DAB) or by immunocytochemical staining for fetal hemoglobin (HbF), This was combined with FISH analysis for both the X- and Y-chromosomes on the same cells. Progressive refinement of the methods increased the number of cases where NRBCs were detected from 53% (DAB) to 75% and 78% for DAB and HbF staining, respectively, with on average 43 NRBCs (range, 1-220), DAB gave a slightly higher yield than HbF in the lower cell count range (

Published
1998

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