Dr Nicola Armstrong

Lecturer

F07 - Carslaw Building
The University of Sydney

Telephone 9351 5794
Fax + 61 2 9351 4534

Website Personal web page

Biographical details

Nicola received her PhD from the Department of Statistics at UC Berkeley. After graduating, she moved to the Netherlands where she spent time as a post doc at Eurandom and the Vrije Universiteit before moving to the Netherlands Cancer Institute in Amsterdam as a senior statistician. On returning to Australia in 2009, she joined the Garvan Institute as a senior bioinformatics officer. In July 2013, she joined the School of Mathematics and Statistics at the University of Sydney where she is a member of the Statistics research group.

Research interests

Nicola's research concerns the application of statistics to genomics. In particular, she is interested in:

  • statistical genetics;
  • epigenetics;
  • genomic data integration.

Genetic networks and sequence motifs

Transcription of each gene is controlled by a regulatory region upstream from the site where transcription begins. There are two elements to this control region: (1) short specific sequences of DNA and (2) transcription factors or gene regulatory elements that recognize and bind to them. The aim is to find the regulatory cis-acting elements or transcription factor binding sites (TFBS) for transcription factors known to be involved in neuronal outgrowth. This information will then be used, along with microarray data, to build a model of the genetic network for the successful regeneration of neurons in the rat.


Design and analysis of microarray experiments

Microarray technology allows the expression levels of thousands of genes to be measured simultaneously. At the same time as the use of microarrays has become more widespread, the complexity of the questions posed by the biologist has also increased. Given the costs involved with a large microarray experiment, as well as other constraints such as limited RNA availability, the issue of good experimental design has become increasingly important. In Amsterdam, I collaborate with biologists at the VU and NIH on the design and analysis of microarray experiments with the aim of identifying differentially expressed genes across various conditions and/or time points.


Crossover interference in linkage analysis

During meiosis, chromosomes replicate, pair and then synapse. Once pairing is complete, crossing over, the reciprocal exchange of chromosomal segments among non-sister chromatids begins. Crossover interference is the non random placement of the crossover points along the length of the chromosome. While many models for this process have been proposed, the majority of genetic mapping studies still ignore the phenomenon of interference and assume the crossover locations come from a Poisson process (leading to Haldane's map function). We have implemented the chi2 model for interference in both simulation studies for breeding programs and in an extension of the Lander-Green algorithm for genetic mapping. Future work will examine the impact of using this more comprehensive model on QTL analysis in experimental crosses.


Teaching and supervision

Timetable

Selected publications

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Book Chapters

  • Zhou, J., Belov, L., Armstrong, N., Christopherson, R. (2013). Antibody Microarrays and Multiplexing. In Xiangdong Wang (Eds.), Bioinformatics of Human Proteomics, (pp. 331-359). Berlin: Springer.

Journals

  • Warton, K., Lin, V., Navin, T., Armstrong, N., Kaplan, W., Ying, K., Gloss, B., Mangs, H., Nair, S., Hacker, N., et al (2014). Methylation-capture and Next-Generation Sequencing of free circulating DNA from human plasma. BMC Genomics, 15(476), 1-13. [More Information]
  • Armstrong, N. (2014). The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging and Behavior, 8, 153-182.
  • Suppiah, V., Armstrong, N., O'Connor, K., Berg, T., Weltman, M., Abate, M., Spengler, U., Bassendine, M., Dore, G., Irving, W., Stewart, G., George, J., Booth, D., Ahlenstiel, G., et al (2013). CCR5-Delta32 genotype does not improve predictive value of IL28B polymorphisms for treatment response in chronic HCV infection. Genes and Immunity, 14(5), 286-290. [More Information]
  • Strbenac, D., Armstrong, N., Yang, J. (2013). Correction: Detection and classification of peaks in 5' cap RNA sequencing data. BMC Genetics, 14(1), Art. 767-1. [More Information]
  • Strbenac, D., Armstrong, N., Yang, J. (2013). Detection and classification of peaks in 5’ cap RNA sequencing data. BMC Genomics, 14(Suppl 5), 1-11. [More Information]
  • Hulf, T., Sibbritt, T., Wiklund, E., Patterson, K., Song, J., Stirzaker, C., Qu, W., Nair, S., Horvath, L., Armstrong, N., et al (2013). Epigenetic-induced repression of microRNA-205 is associated with MED1 activation and a poorer prognosis in localized prostate cancer. Oncogene, 32(23), 2891-2899. [More Information]
  • Dobson-Stone, C., Polly, P., Korgaonkar, M., Williams, L., Gordon, E., Schofield, P., Mather, K., Armstrong, N., Wen, W., Sachdev, P., et al (2013). GSK3B and MAPT polymorphisms are associated with grey matter and intracranial volume in healthy individuals. PLoS One, 8(8), 1-7. [More Information]
  • Parnell, G., Tang, B., Nalos, M., Armstrong, N., Huang, S., Booth, D., McLean, A. (2013). Identifying key regulatory genes in the whole blood of septic patients to monitor underlying immune dysfunctions. Shock (Philadelphia), 40(3), 166-174. [More Information]
  • Parnell, G., McLean, A., Booth, D., Armstrong, N., Nalos, M., Huang, S., Manak, J., Tang, W., Tam, O., Chan, S., Tang, B. (2012). A distinct influenza infection signature in the blood transcriptome of patients with severe community-acquired pneumonia. Critical Care, 16(4), 1-12. [More Information]
  • Kao, S., Armstrong, N., Condon, B., Griggs, K., McCaughan, B., Maltby, S., Wilson, A., Henderson, D., Klebe, S. (2012). Aquaporin 1 is an Independent Prognostic Factor in Pleural Malignant Mesothelioma. Cancer, 118(11), 2952-2961. [More Information]
  • Birzniece, V., Meinhardt, U., Gibney, J., Johannsson, G., Armstrong, N., Baxter, R., Ho, K. (2012). Differential Effects of Raloxifene and Estrogen on Body Composition in Growth Hormone-Replaced Hypopituitary Women. Journal of Clinical Endocrinology and Metabolism, 97(3), 1005-1012. [More Information]
  • Kalyuga, M., Gallego-Ortega, D., Lee, H., Roden, D., Cowley, M., Caldon, C., Stone, A., Allerdice, S., Valdes-Mora, F., Launchbury, R., Naylor, M., et al (2012). ELF5 Suppresses Estrogen Sensitivity and Underpins the Acquisition of Antiestrogen Resistance in Luminal Breast Cancer. PLoS Biology, 10(12), 1-17. [More Information]
  • Kirschner, M., Cheng, V., Badrian, B., Kao, S., Creaney, J., Edelman, J., Armstrong, N., Vallely, M., Musk, A., Robinson, B., McCaughan, B., van Zandwijk, N., Reid, G., et al (2012). Increased Circulating miR-625-3p: A Potential Biomarker for Patients With Malignant Pleural Mesothelioma. Journal of Thoracic Oncology, 7(7), 1184-1191. [More Information]
  • Kirschner, M., Kao, S., Edelman, J., Armstrong, N., Vallely, M., van Zandwijk, N., Reid, G. (2011). Haemolysis during Sample Preparation Alters microRNA Content of Plasma. PLoS One, 6(9), 1-9. [More Information]
  • Suppiah, V., Gaudieri, S., Armstrong, N., O'Connor, K., Berg, T., Weltman, M., Abate, M., Spengler, U., Bassendine, M., Dore, G., Ahlenstiel, G., Stewart, G., George, J., Booth, D., et al (2011). IL28B, HLA-C, and KIR Variants Additively Predict Response to Therapy in Chronic Hepatitis C Virus Infection in a European Cohort: A Cross-Sectional Study. PLoS Medicine, 8(9), e1001092-1-e1001092-8. [More Information]
  • Kao, S., Klebe, S., Henderson, D., Reid, G., Chatfield, M., Armstrong, N., Yan, T., Vardy, J., Clarke, S., van Zandwijk, N., McCaughan, B. (2011). Low Calretinin Expression and High Neutrophil-To-Lymphocyte Ratio Are Poor Prognostic Factors in Patients with Malignant Mesothelioma Undergoing Extrapleural Pneumonectomy. Journal of Thoracic Oncology, 6(11), 1923-1929. [More Information]
  • Kao, S., Griggs, K., Lee, K., Armstrong, N., Clarke, S., Vardy, J., van Zandwijk, N., Burn, J., McCaughan, B., Henderson, D., et al (2011). Validation of a minimal panel of antibodies for the diagnosis of malignant pleural mesothelioma. Pathology, 43(4), 313-317. [More Information]
  • Kao, S., Lee, K., Armstrong, N., Clarke, S., Vardy, J., van Zandwijk, N., Reid, G., Burn, J., McCaughan, B., Henderson, D., et al (2011). Validation of tissue microarray technology in malignant pleural mesothelioma. Pathology, 43(2), 128-132. [More Information]
  • Gerlach, C., van Heijst, J., Swart, E., Sie, D., Armstrong, N., Kerkhoven, R., Zehn, D., Bevan, M., Schepers, K., Schumacher, T. (2010). One Naive T Cell, Multiple Fates in CD8+ T Cell Differentiation. The Journal of Experimental Medicine, 207(6), 1235-1246. [More Information]
  • Gandhi, K., McKay, F., Cox, M., Riveros, C., Armstrong, N., Heard, R., Vucic, S., Williams, D., Stankovich, J., Brown, M., Stewart, G., Booth, D., et al (2010). The multiple sclerosis whole blood mRNA transcriptome and genetic associations indicate dysregulation of specific T cell pathways in pathogenesis. Human Molecular Genetics, 19(11), 2134-2143. [More Information]
  • Mook, S., Schmidt, M., Rutgers, E., van de Velde, A., Visser, O., Rutgers, S., Armstrong, N., van’t Veer, L., Ravdin, P. (2009). Calibration and discriminatory accuracy of the web-based tool Adjuvant! in a hospital-based cohort of 5380 Dutch breast cancer patients. The Lancet Oncology, 10(11), 1070-1076.
  • Kreike, B., Halfwerk, H., Armstrong, N., Bult, P., Foekens, J., Veltkamp, S., Nuyten, D., Bartelink, H., van de Vijver, M. (2009). Local Recurrence after Breast-Conserving Therapy in Relation to Gene Expression Patterns in a Large Series of Patients. Clinical Cancer Research, 15(12), 4181-4190. [More Information]
  • Kok, M., Koomstra, R., Margarido, T., Fles, R., Armstrong, N., Linn, S., van’t Veer, L., Weigelt, B. (2009). Mammosphere-derived gene set predicts outcome in patients with ER-positive breast cancer. Journal of Pathology, 218(3), 316-326. [More Information]
  • van den Broek, G., Wildeman, M., Rasch, C., Armstrong, N., Schuuring, E., Begg, A., Looijenga, L., Scheper, R., et al (2009). Molecular markers predict outcome in squamous cell carcinoma of the head and neck after concomitant cisplatin-based chemoradiation. International Journal of Cancer, 124(11), 2643-2650. [More Information]
  • Reyal, F., van Vliet, M., Armstrong, N., Horlings, H., de Visser, K., Kok, M., Teschendorff, A., Mook, S., van’t Veer, L., et al (2008). A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the Proliferation, Immune response and RNA splicing modules in breast cancer. Breast Cancer Research, 10(6), 1-15. [More Information]
  • Armstrong, N. (2008). The changing focus of microarray analysis. Statistica Neerlandica, 62(3), 364-373. [More Information]
  • Stam, F., MacGillavry, H., Armstrong, N., de Gunst, M., Zhang, Y., van Kesteren, R., Smit, A., Verhaagen, J. (2007). Identification of candidate transcriptional modulators involved in successful regeneration after nerve injury. European Journal of Neuroscience, 25(12), 3629-3637. [More Information]
  • Armstrong, N., McPeek, M., Speed, T. (2006). Incorporating interference into linakge analysis for experimental crosses. Biostatistics, 7(3), 374-386.
  • Armstrong, N., Brodnicki, T., Speed, T. (2006). Mind the gap: analysis of marker-assisted breeding strategies for inbred mouse strains. Mammalian Genome, 17(4), 273-287. [More Information]
  • Armstrong, N., Van De Wiel, M. (2004). Microarray data analysis: from hypotheses to conclusions using gene expression data. Cellular Oncology, 26(5-6), 279-290.
  • Rabbee, N., Speca, D., Armstrong, N., Speed, T. (2004). Power calculations for selective genotyping in QTL mapping in backcross mice. Genetical Research, 84(2), 103-108. [More Information]

2014

  • Warton, K., Lin, V., Navin, T., Armstrong, N., Kaplan, W., Ying, K., Gloss, B., Mangs, H., Nair, S., Hacker, N., et al (2014). Methylation-capture and Next-Generation Sequencing of free circulating DNA from human plasma. BMC Genomics, 15(476), 1-13. [More Information]
  • Armstrong, N. (2014). The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging and Behavior, 8, 153-182.

2013

  • Zhou, J., Belov, L., Armstrong, N., Christopherson, R. (2013). Antibody Microarrays and Multiplexing. In Xiangdong Wang (Eds.), Bioinformatics of Human Proteomics, (pp. 331-359). Berlin: Springer.
  • Suppiah, V., Armstrong, N., O'Connor, K., Berg, T., Weltman, M., Abate, M., Spengler, U., Bassendine, M., Dore, G., Irving, W., Stewart, G., George, J., Booth, D., Ahlenstiel, G., et al (2013). CCR5-Delta32 genotype does not improve predictive value of IL28B polymorphisms for treatment response in chronic HCV infection. Genes and Immunity, 14(5), 286-290. [More Information]
  • Strbenac, D., Armstrong, N., Yang, J. (2013). Correction: Detection and classification of peaks in 5' cap RNA sequencing data. BMC Genetics, 14(1), Art. 767-1. [More Information]
  • Strbenac, D., Armstrong, N., Yang, J. (2013). Detection and classification of peaks in 5’ cap RNA sequencing data. BMC Genomics, 14(Suppl 5), 1-11. [More Information]
  • Hulf, T., Sibbritt, T., Wiklund, E., Patterson, K., Song, J., Stirzaker, C., Qu, W., Nair, S., Horvath, L., Armstrong, N., et al (2013). Epigenetic-induced repression of microRNA-205 is associated with MED1 activation and a poorer prognosis in localized prostate cancer. Oncogene, 32(23), 2891-2899. [More Information]
  • Dobson-Stone, C., Polly, P., Korgaonkar, M., Williams, L., Gordon, E., Schofield, P., Mather, K., Armstrong, N., Wen, W., Sachdev, P., et al (2013). GSK3B and MAPT polymorphisms are associated with grey matter and intracranial volume in healthy individuals. PLoS One, 8(8), 1-7. [More Information]
  • Parnell, G., Tang, B., Nalos, M., Armstrong, N., Huang, S., Booth, D., McLean, A. (2013). Identifying key regulatory genes in the whole blood of septic patients to monitor underlying immune dysfunctions. Shock (Philadelphia), 40(3), 166-174. [More Information]

2012

  • Parnell, G., McLean, A., Booth, D., Armstrong, N., Nalos, M., Huang, S., Manak, J., Tang, W., Tam, O., Chan, S., Tang, B. (2012). A distinct influenza infection signature in the blood transcriptome of patients with severe community-acquired pneumonia. Critical Care, 16(4), 1-12. [More Information]
  • Kao, S., Armstrong, N., Condon, B., Griggs, K., McCaughan, B., Maltby, S., Wilson, A., Henderson, D., Klebe, S. (2012). Aquaporin 1 is an Independent Prognostic Factor in Pleural Malignant Mesothelioma. Cancer, 118(11), 2952-2961. [More Information]
  • Birzniece, V., Meinhardt, U., Gibney, J., Johannsson, G., Armstrong, N., Baxter, R., Ho, K. (2012). Differential Effects of Raloxifene and Estrogen on Body Composition in Growth Hormone-Replaced Hypopituitary Women. Journal of Clinical Endocrinology and Metabolism, 97(3), 1005-1012. [More Information]
  • Kalyuga, M., Gallego-Ortega, D., Lee, H., Roden, D., Cowley, M., Caldon, C., Stone, A., Allerdice, S., Valdes-Mora, F., Launchbury, R., Naylor, M., et al (2012). ELF5 Suppresses Estrogen Sensitivity and Underpins the Acquisition of Antiestrogen Resistance in Luminal Breast Cancer. PLoS Biology, 10(12), 1-17. [More Information]
  • Kirschner, M., Cheng, V., Badrian, B., Kao, S., Creaney, J., Edelman, J., Armstrong, N., Vallely, M., Musk, A., Robinson, B., McCaughan, B., van Zandwijk, N., Reid, G., et al (2012). Increased Circulating miR-625-3p: A Potential Biomarker for Patients With Malignant Pleural Mesothelioma. Journal of Thoracic Oncology, 7(7), 1184-1191. [More Information]

2011

  • Kirschner, M., Kao, S., Edelman, J., Armstrong, N., Vallely, M., van Zandwijk, N., Reid, G. (2011). Haemolysis during Sample Preparation Alters microRNA Content of Plasma. PLoS One, 6(9), 1-9. [More Information]
  • Suppiah, V., Gaudieri, S., Armstrong, N., O'Connor, K., Berg, T., Weltman, M., Abate, M., Spengler, U., Bassendine, M., Dore, G., Ahlenstiel, G., Stewart, G., George, J., Booth, D., et al (2011). IL28B, HLA-C, and KIR Variants Additively Predict Response to Therapy in Chronic Hepatitis C Virus Infection in a European Cohort: A Cross-Sectional Study. PLoS Medicine, 8(9), e1001092-1-e1001092-8. [More Information]
  • Kao, S., Klebe, S., Henderson, D., Reid, G., Chatfield, M., Armstrong, N., Yan, T., Vardy, J., Clarke, S., van Zandwijk, N., McCaughan, B. (2011). Low Calretinin Expression and High Neutrophil-To-Lymphocyte Ratio Are Poor Prognostic Factors in Patients with Malignant Mesothelioma Undergoing Extrapleural Pneumonectomy. Journal of Thoracic Oncology, 6(11), 1923-1929. [More Information]
  • Kao, S., Griggs, K., Lee, K., Armstrong, N., Clarke, S., Vardy, J., van Zandwijk, N., Burn, J., McCaughan, B., Henderson, D., et al (2011). Validation of a minimal panel of antibodies for the diagnosis of malignant pleural mesothelioma. Pathology, 43(4), 313-317. [More Information]
  • Kao, S., Lee, K., Armstrong, N., Clarke, S., Vardy, J., van Zandwijk, N., Reid, G., Burn, J., McCaughan, B., Henderson, D., et al (2011). Validation of tissue microarray technology in malignant pleural mesothelioma. Pathology, 43(2), 128-132. [More Information]

2010

  • Gerlach, C., van Heijst, J., Swart, E., Sie, D., Armstrong, N., Kerkhoven, R., Zehn, D., Bevan, M., Schepers, K., Schumacher, T. (2010). One Naive T Cell, Multiple Fates in CD8+ T Cell Differentiation. The Journal of Experimental Medicine, 207(6), 1235-1246. [More Information]
  • Gandhi, K., McKay, F., Cox, M., Riveros, C., Armstrong, N., Heard, R., Vucic, S., Williams, D., Stankovich, J., Brown, M., Stewart, G., Booth, D., et al (2010). The multiple sclerosis whole blood mRNA transcriptome and genetic associations indicate dysregulation of specific T cell pathways in pathogenesis. Human Molecular Genetics, 19(11), 2134-2143. [More Information]

2009

  • Mook, S., Schmidt, M., Rutgers, E., van de Velde, A., Visser, O., Rutgers, S., Armstrong, N., van’t Veer, L., Ravdin, P. (2009). Calibration and discriminatory accuracy of the web-based tool Adjuvant! in a hospital-based cohort of 5380 Dutch breast cancer patients. The Lancet Oncology, 10(11), 1070-1076.
  • Kreike, B., Halfwerk, H., Armstrong, N., Bult, P., Foekens, J., Veltkamp, S., Nuyten, D., Bartelink, H., van de Vijver, M. (2009). Local Recurrence after Breast-Conserving Therapy in Relation to Gene Expression Patterns in a Large Series of Patients. Clinical Cancer Research, 15(12), 4181-4190. [More Information]
  • Kok, M., Koomstra, R., Margarido, T., Fles, R., Armstrong, N., Linn, S., van’t Veer, L., Weigelt, B. (2009). Mammosphere-derived gene set predicts outcome in patients with ER-positive breast cancer. Journal of Pathology, 218(3), 316-326. [More Information]
  • van den Broek, G., Wildeman, M., Rasch, C., Armstrong, N., Schuuring, E., Begg, A., Looijenga, L., Scheper, R., et al (2009). Molecular markers predict outcome in squamous cell carcinoma of the head and neck after concomitant cisplatin-based chemoradiation. International Journal of Cancer, 124(11), 2643-2650. [More Information]

2008

  • Reyal, F., van Vliet, M., Armstrong, N., Horlings, H., de Visser, K., Kok, M., Teschendorff, A., Mook, S., van’t Veer, L., et al (2008). A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the Proliferation, Immune response and RNA splicing modules in breast cancer. Breast Cancer Research, 10(6), 1-15. [More Information]
  • Armstrong, N. (2008). The changing focus of microarray analysis. Statistica Neerlandica, 62(3), 364-373. [More Information]

2007

  • Stam, F., MacGillavry, H., Armstrong, N., de Gunst, M., Zhang, Y., van Kesteren, R., Smit, A., Verhaagen, J. (2007). Identification of candidate transcriptional modulators involved in successful regeneration after nerve injury. European Journal of Neuroscience, 25(12), 3629-3637. [More Information]

2006

  • Armstrong, N., McPeek, M., Speed, T. (2006). Incorporating interference into linakge analysis for experimental crosses. Biostatistics, 7(3), 374-386.
  • Armstrong, N., Brodnicki, T., Speed, T. (2006). Mind the gap: analysis of marker-assisted breeding strategies for inbred mouse strains. Mammalian Genome, 17(4), 273-287. [More Information]

2004

  • Armstrong, N., Van De Wiel, M. (2004). Microarray data analysis: from hypotheses to conclusions using gene expression data. Cellular Oncology, 26(5-6), 279-290.
  • Rabbee, N., Speca, D., Armstrong, N., Speed, T. (2004). Power calculations for selective genotyping in QTL mapping in backcross mice. Genetical Research, 84(2), 103-108. [More Information]

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