Granted Patent
B2
US 12,480,960 · App. 17/422,033 · Granted Nov 25, 2025
Compositions and methods for predicting lung function decline in idiopathic pulmonary fibrosis
Assignee:
University of Virginia Patent Foundation
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Abstract
Provided are methods for generating prognostic signatures for subject diagnosed with Idiopathic Pulmonary Fibrosis (IPF) with respect to decline in lung Forced Vital Capacity (FVC). The methods can include determining first expression levels for one or more genes as set forth herein in a first biological sample obtained from a subject diagnosed with IPF, determining a second expression level for the same one or more genes in a second biological sample obtained from the subject, and comparing the first and second expression levels for the one or more genes to provide a prognostic signature. The first and second biological samples can include peripheral blood mononuclear cells (PBMCs) and/or nucleic acids extracted from PBMCs. Also provided are methods for classifying subjects with IPF as being at risk for FVC decline, for identifying and treating at risk subjects, and for monitoring the progress of treatments.
Claims (17)
1 . A method for identifying and treating a subject diagnosed with Idiopathic Pulmonary Fibrosis (IPF) at risk for a decline in lung Forced Vital Capacity (FVC), the method comprising:
(a) determining first expression levels for a set of genes in a first biological sample obtained from the subject diagnosed with IPF to establish baseline expression levels for the set of genes, wherein the set of genes is selected from the group consisting of:
(i) APTX, CNR2, GYPA, ITLN1, MAZ, MSR1, NT5E, PAWR, PLA2G4A, and PNMA5;
(ii) APTX, ATP6AP1L, ITLN1, LINC00319, MAZ, MSR1, NT5E, PCDHB15, RAB3C, SSU72P8, and TP62;
(iii) APTX, CNR2, GABRR1, GPR39, GYPA, HBB, ITLN1, MAZ, MSR1, NT5E, PAWR, PCDHB15, PLA2G4A, PNMA5, RLBP1, and SSU72P8; and
(iv) APTX, ATP6AP1L, CNR2, FAM111B, GABRR1, GPR39, GYPA, HBB, IGLC1, ITLN1, LINC00319, MAZ, MSR1, NT5E, PAWR, PCDHB15, PLA2G4A, PLCL1, PNMA5, RAB3C, RBM43, RLBP1, SSU72P8, TP63, and ZNF252P;
(b) determining second expression levels for the set of genes in a second biological sample obtained from the subject, wherein the first and second biological samples comprise peripheral blood mononuclear cells (PBMCs) and/or nucleic acids extracted from PBMCs;
(c) comparing the first and second expression levels for the set of genes to create an FVC-gene predictor score; and
(d) treating the subject based on the FVC-gene predictor score with a treatment selected from the group consisting of lung transplantation and a drug therapy, wherein the drug therapy comprises administering to the subject a pharmaceutical composition in an amount and via a route of administration effective to delay or prevent the development of FVC decline in the subject.
2 . The method of claim 1 , wherein the pharmaceutical composition comprises pirfenidone, nintedanib, or a combination thereof.
3 . The method of claim 1 , wherein the subject is a human.
4 . The method of claim 1 , comprising determining the first and second expression levels for each gene in the set of APTX, ATP6AP1L, CNR2, FAM111B, GABRR1, GPR39, GYPA, HBB, IGLC1, ITLN1, LINC00319, MAZ, MSR1, NT5E, PAWR, PCDHB15, PLA2G4A, PLCL1, PNMA5, RAB3C, RBM43, RLBP1, SSU72P8, TP63, and ZNF252P.
5 . The method of claim 1 , wherein the second biological sample is obtained from the subject at a time from about 4 to about 12 months subsequent to when the first biological sample was obtained from the subject.
6 . The method of claim 1 , wherein one or both of the determining steps comprise a technique selected from the group consisting of RNA-seq analysis, quantitative polymerase chain reaction (PCR), quantitative reverse transcription PCR (qRT-PCR), a nucleic acid or protein array, or any combination thereof.
7 . The method of claim 1 , wherein the comparing of the first and second expression levels for the set of genes comprises comparing normalized expression levels for each gene in the first and second biological samples to generate a fold-increase and/or a fold-decrease of the expression level in the second biological sample relative to the first biological sample for each gene.
8 . The method of claim 7 , wherein the comparing further comprises summing each fold-increase and/or fold-decrease of the expression level to produce an FVC-gene predictor score for the subject.
9 . The method of claim 8 , wherein the summing is performed after multiplying each fold-increase and/or fold-decrease of the expression level by a weighting value to produce a weighted FVC-gene predictor score for the subject.
Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST
Recorded Sep 19, 2024
From: NOTH, IMRE
To: UNIVERSITY OF VIRGINIA
Reel/Frame 068632/0823 →
ASSIGNMENT OF ASSIGNOR'S INTEREST
Recorded Sep 19, 2024
From: UNIVERSITY OF VIRGINIA
To: UNIVERSITY OF VIRGINIA PATENT FOUNDATION
Reel/Frame 068632/0857 →
Continuity (3)
Provisional Application
62849630
· May 17, 2019
Provisional Application
62791083
· Jan 11, 2019
References Cited (130)
US 3974281A
· Gadekar
· 1976
[cited by applicant]
US 5800992A
· Fodor et al.
· 1998
[cited by applicant]
US 6004755A
· Wang
· 1999
[cited by applicant]
US 6013449A
· Hacia et al.
· 2000
[cited by applicant]
US 6020135A
· Levine et al.
· 2000
[cited by applicant]
US 6033860A
· Lockhart et al.
· 2000
[cited by applicant]
US 6040138A
· Lockhart et al.
· 2000
[cited by applicant]
US 6177248B1
· Oliner et al.
· 2001
[cited by applicant]
US 6251601B1
· Bao et al.
· 2001
[cited by applicant]
US 6309822B1
· Fodor et al.
· 2001
[cited by applicant]
US 6762180B1
· Roth et al.
· 2004
[cited by applicant]
US 7824856B2
· Monforte
· 2010
[cited by applicant]
US 8592462B2
· Bradford et al.
· 2013
[cited by applicant]
US 9884802B2
· Gagnon et al.
· 2018
[cited by applicant]
US 9920367B2
· Bhargava et al.
· 2018
[cited by applicant]
US 20100120097A1
· Matz et al.
· 2010
[cited by applicant]
US 20110189679A1
· Kurn et al.
· 2011
[cited by applicant]
US 20130116166A1
· Desai
· 2013
[cited by examiner]
US 20150133333A1
· Garcia et al.
· 2015
[cited by applicant]
US 20150307874A1
· Jaitin et al.
· 2015
[cited by applicant]
US 20180064695A1
· Bradford et al.
· 2018
[cited by applicant]
US 20180169084A1
· Bradford
· 2018
[cited by applicant]
US 20190282565A1
· Liang
· 2019
[cited by applicant]
EP 2860525A1
· 2015
[cited by applicant]
EP 3908668
· 2021
[cited by applicant]
WO WO2013148232A1
· 2013
[cited by applicant]
WO WO2016042114A1
· 2016
[cited by applicant]
WO WO2020146887A1
· 2020
[cited by applicant]
Adams et al., Am. J. Respir. Crit. Care Med., 2016, vol. 194(3): 374-376.
[cited by examiner]
International Search Report and Written Opinion corresponding to International Patent Application No. PCT/US2020/013367 dated Apr. 1, 2020.
[cited by applicant]
Communication of Publication corresponding to European Patent Application Serial No. 20738547.7 dated Oct. 20, 2021.
[cited by applicant]
Search Report corresponding to EP Application No. 20738547.7 dated Oct. 7, 2022.
[cited by applicant]
Bauer et al. (2015) “A Novel Genomic Signature with Translational Significance for Human Idiopathic Pulmonary Fibrosis,” American Journal of Respiratory Cell and Molecular Biology, vol. 52, No. 2, pp. 217-231.
[cited by applicant]
Herazo-Maya et al. (2013) “Peripheral Blood Mononuclear Cell Gene Expression Profiles Predict Poor Outcome in Idiopathic Pulmonary Fibrosis,” Science Translational Medicine, vol. 5, No. 205, pp. 1-23.
[cited by applicant]
Herazo-Maya et al. (2017) “Validation of a 52-Gene Risk Profile for Outcome Prediction in Patients with Idiopathic Pulmonary Fibrosis: an International, Multicentre, Cohort Study,” The Lancet, Respiratory Medicine, vol.…
[cited by applicant]
Office Action corresponding to European Patent Application No. 20738547.7-1111 dated Oct. 29, 2024, pp. 4.
[cited by applicant]
Wirsdorfer & Jendrossek (2016) The Role of Lymphocytes in Radiotherapy-Induced Adverse Late Effects in the Lung. Front Immunol 7:591.
[cited by applicant]
Trapnell et al. (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25:1105-1111.
[cited by applicant]
Tibshirani et al. (2012) Strong rules for discarding predictors in lasso-type problems. J R Stat Soc Series B Stat Methodol 74:245-266.
[cited by applicant]
Tajiri et al. (2015) Serum level of periostin can predict long-term outcome of idiopathic pulmonary fibrosis. Respir Investig 53:73-81.
[cited by applicant]
Suykens & Vandewalle (1999) Least Squares Support Vector Machine Classifiers. Neural Processing Letters 9:293-300.
[cited by applicant]
Subramanian et al. (2005)Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci US A 102:15545-15550.
[cited by applicant]
Smyth (2004) Linear models and empirical Bayes methods for assesing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3 :Article3.
[cited by applicant]
Simon et al. (2011) Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent. J Stat Softw 3 9: 1-13.
[cited by applicant]
Schmidt et al. (2014) Predicting pulmonary fibrosis disease course from past trends in pulmonary function. Chest 145:579-585.
[cited by applicant]
Rosas et al. (2008) MMP1 and MMP7 as potential peripheral blood biomarkers in idiopathic pulmonary fibrosis. PLoS Med 5:e93.
[cited by applicant]
Robinson et al. (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26:139-140.
[cited by applicant]
Robinson & Oshlack (2010) A scaling normalization method for differential expression analysis of RNA-seg data. Genome Biol 11 :R25.
[cited by applicant]
Robin et al. (2011) pROC: an open-source package for Rand S+ to analyze and compare ROC curves. BMC Bioinformatics 12:77.
[cited by applicant]
Richeldi et al. (2014) Efficacy and safety ofnintedanib in idiopathic pulmonary fibrosis. N Engl J Med 370:2071-2082.
[cited by applicant]
Richards et al. (2012) Plasma proteins for risk prediction in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 185:1329-1330.
[cited by applicant]
Raghu et al. (2011) An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management. Am J Respir Crit Care Med 183:788-824.
[cited by applicant]
Prasse et al. (2009) Serum CC-chemokine ligand 18 concentration predicts outcome in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 179: 717-723.
[cited by applicant]
Peljto et al. (2013) Association between the MUC5B promoter polymorphism and survival in patients with idiopathic pulmonary fibrosis. JAMA 309:2232-2239.
[cited by applicant]
Pardo et al. (2016) Role of matrix metalloproteinases in the pathogenesis of idiopathic pulmonary fibrosis. Respir Res 17:23.
[cited by applicant]
Ohta et al. (2017) The usefulness of monomeric periostin as a biomarker for idiopathic pulmonary fibrosis. PLoS One 12:e0174547.
[cited by applicant]
O'Dwyer et al. (2017) The peripheral blood proteome signature of idiopathic pulmonary fibrosis is distinct from normal and is associated with novel immunological processes. Sci Rep 7:46560.
[cited by applicant]
Noth et al. (2012) Idiopathic Pulmonary Fibrosis Clinical Research N. A placebo-controlled randomized trial of warfarin in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 186:88-95.
[cited by applicant]
Neighbors et al. (2018) Prognostic and predictive biomarkers for patients with idiopathic pulmonary fibrosis treated with pirfenidone: post-hoc assessment of the Capacity and Ascend trials. Lancet Respir Med 6:615-626.
[cited by applicant]
Naik et al. (2012) Periostin promotes fibrosis and predicts progression in patients with idiopathic pulmonary fibrosis. Am J Physiol Lung Cell Mol Physiol 303:L1046-1056.
[cited by applicant]
Mortazavi et al. (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5:621-628.
[cited by applicant]
Miller et al. (2005b) Standardisation of spirometry. Eur Respir J 26:319-338.
[cited by applicant]
Miller et al. (2005a) General considerations for lung function testing. Eur Respir J 26:153-161.
[cited by applicant]
Masel & Siegal (2009) Robustness: mechanisms and consequences. Trends Genet 25:395-403.
[cited by applicant]
Maher et al. (2017) An epithelial biomarker signature for idiopathic pulmonary fibrosis: an analysis from the multicentre Profile cohort study. LancetRespir Med 5:946-955.
[cited by applicant]
Macintyre et al. (2005) Standardisation of the single-breath determination of carbon monoxide uptake in the lung. Eur Respir J 26:720-735.
[cited by applicant]
Love et al. (2014) Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Genome Biol 15:550.
[cited by applicant]
Li (2008) Automating dChip: toward reproducible sharing of microarray data analysis. BMC Bioinformatics 9:231.
[cited by applicant]
Ley et al. (2016) Predictors of Mortality Poorly Predict Common Measures of Disease Progression in Idiopathic Pulmonary Fibrosis. Am J Respir Crit Care Med 194:711-718.
[cited by applicant]
Ley et al. (20 14) Molecular biomarkers in idiopathic pulmonary fibrosis. Am J Physiol Lung Cell Mol Physiol307:L681-691.
[cited by applicant]
Law et al. (2014) voom: Precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 15:R29.
[cited by applicant]
King et al. (2014) A phase 3 trial of pirfenidone in patients with idiopathic pulmonary fibrosis. N Engl J Med 370:2083-2092.
[cited by applicant]
Karlin & Altschul (1993) Applications and statistics for multiple high-scoring segments in molecular sequences. Proc Natl Acad Sci US A 90:5873-5877.
[cited by applicant]
Karlin & Altschul (1990) Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes. Proc Natl A cad Sci U S A 87:2264-2268.
[cited by applicant]
Karimi-Shah & Chowdhury (2015) Forced vital capacity in idiopathic pulmonary fibrosis-FDA review of pirfenidone and nintedanib. N Engl J Med 372:1189-1191.
[cited by applicant]
Kang et al. (2007) Transforming growth factor (TGF)-beta1 stimulates pulmonary fibrosis and inflammation via a Bax-dependent, bid-activated pathway that involves matrix metalloproteinase-12. J Biol Chern 282:7723-7732.
[cited by applicant]
Kaner et al. (2019) Design of IPF Clinical Trials in the Era of Approved Therapies. Am J Respir Crit Care Med 200:133-139.
[cited by applicant]
Kaimal et al. (2010) ToppCluster: a multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems. Nucleic Acids Res 38: W96-102.
[cited by applicant]
Jegal et al. (2005) Physiology is a stronger predictor of survival than pathology in fibrotic interstitial pneumonia. Am J Respir Crit Care Med 171:639-644.
[cited by applicant]
Irizarry et al. (2003) Exploration, normalization, and summanes of high density oligonucleotide array probe level data. Biostatistics 4:249-264.
[cited by applicant]
Idiopathic Pulmonary Fibrosis Clinical Research Network et al. (2012) Prednisone, azathioprine, and N-acetylcysteine for pulmonary fibrosis. N Engl J Med 366:1968-1977.
[cited by applicant]
Idiopathic Pulmonary Fibrosis Clinical Research Network et al. (2010) A controlled trial of sildenafil in advanced idiopathic pulmonary fibrosis. N Engl J Med 363:620-628.
[cited by applicant]
Hyslop & White (2009) Estimating precision using duplicate measurements. J Air Waste Manag Assoc 59:1032-1039.
[cited by applicant]
Huang et al. (2017) Microbes Are Associated with Host Innate Immune Response in Idiopathic Pulmonary Fibrosis. Am J Respir Crit Care Med 196:208-219.
[cited by applicant]
Hoffmann-Vold et al. (2016) High Level of Chemokine CCL18 Is Associated With Pulmonary Function Deterioration, Lung Fibrosis Progression, and Reduced Survival in Systemic Sclerosis. Chest 150:299-306.
[cited by applicant]
Hamai et al. (2016) Comparative Study of Circulating MMP-7, CCL18, KL-6, SP-A, and SP-D as Disease Markers of Idiopathic Pulmonary Fibrosis. Dis Markers 2016; 2016: 4759040.
[cited by applicant]
Gu et al. (2016) Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 32:2847-2849.
[cited by applicant]
Greene et al. (2002) Serum surfactant proteins-A and -D as biomarkers in idiopathic pulmonary fibrosis. Eur Respir J 19:439-446.
[cited by applicant]
Gautier et al. (2004) affy—analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 20:307-315.
[cited by applicant]
Friedman et al. (2010) Regularization Paths for Generalized Linear Models via Coordinate Descent. J Stat Softw 33:1-22.
[cited by applicant]
Flaherty et al. (2007) Idiopathic interstitial pneumonia: do community and academic physicians agree on diagnosis? Am J Respir Crit Care Med 175:1054-1060.
[cited by applicant]
Flaherty et al. (2004) Idiopathic interstitial pneumoma: what is the effect of a multidisciplinary approach to diagnosis? Am J Respir Crit Care Med 170:904-910.
[cited by applicant]
DuBois et al. (2011) Forced vital capacity in patients with idiopathic pulmonary fibrosis: test properties and minimal clinically important difference. Am J Respir Crit Care Med 184:1382-1389.
[cited by applicant]
Dobin et al. (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15-21.
[cited by applicant]
Chilosi et al. (2002) Abnormal re-epithelialization and lung remodeling in idiopathic pulmonary fibrosis: the role of deltaN-p63. Lab Invest 82:1335-1345.
[cited by applicant]
Benjamini & Hochberg (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc 57:289-300.
[cited by applicant]
Ballman et al. (2004) Faster cyclic loess: normalizing RNA arrays via linear models. Bioinformatics 20:2778-2786.
[cited by applicant]
Armstrong et al. (2017) Serum Matrix Metalloproteinase-7, Respiratory Symptoms, and Mortality in Community-Dwelling Adults. MESA (Multi-Ethnic Study of Atherosclerosis). Am J Respir Crit Care Med 196:1311-1317.
[cited by applicant]
Anders et al. (2014) HTSeq-a Python framework to work with high-throughput sequencing data. Bioinformatics 31:166-169.
[cited by applicant]
American Thoracic Society & European Respiratory Society (2002) American Thoracic Society/European Respiratory Society International Multidisciplinary Consensus Classification of the Idiopathic Interstitial Pneumonias. …
[cited by applicant]
Altschul et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389-3402.
[cited by applicant]
Altschul et al. (1990b) Protein database searches for multiple alignments. Proc Natl Acad Sci US A 87:14:5509-5513.
[cited by applicant]
Altschul et al. (1990a) Basic local alignment search tool. J Mol Biol 215:403-410.
[cited by applicant]
Alexa et al. (2006) Improved scoring of functional groups from gene expression data by decorrelating GO graph structure. Bioinformatics 22:1600-1607.
[cited by applicant]
Huang Y, Ma SF, Vij R, Oldham JM, Herazo-Maya J, Broderick SM, Strek ME, White SR, Hogarth DK, Sandbo NK, Lussier YA, Gibson KF, Kaminski N, Garcia JG, Noth I. A functional genomic model for predicting prognosis in idio…
[cited by applicant]
Swigris JJ, Kuschner WG, Kelsey JL, Gould MK. Idiopathic pulmonary fibrosis: challenges and opportunities for the clinician and investigator. Chest. 2005;127(1):275-83.
[cited by applicant]
Du Bois RM , Weycker D , Albera C , et al . Ascertainment of individual risk of mortality for patients with idiopathic pulmonary fibrosis . Am J Respir Crit Care.
[cited by applicant]
Whitney AR, Diehn M, Popper SJ, Alizadeh AA, Boldrick JC, Relman DA, Brown PO. Individuality and variation in gene expression patterns in human blood. Proc Natl Acad Sci U S A. Feb. 18, 2003;100(4):1896-901.
[cited by applicant]
Wright, F. A. et al. Heritability and genomics of gene expression in peripheral blood. Nat Genet 46, 430-437 (2014).
[cited by applicant]
Hofmann T, Klenow S, Borowicki A, Gill CI, Pool-Zobel BL, Glei M. Gene expression profiles in human peripheral blood mononuclear cells as biomarkers for nutritional in vitro and in vivo investigations. Genes Nutr. Dec. …
[cited by applicant]
Kavcic P, Rojc B, Dolenc-Groselj L, Claustrat B, Fujs K, Poljak M. The impact of sleep deprivation and nighttime light exposure on clock gene expression in humans. Croat Med J. Oct. 15, 2011;52(5):594-603.
[cited by applicant]
Eady JJ, Wortley GM, Wormstone YM, Hughes JC, Astley SB, Foxall RJ, Doleman JF, Elliott RM. Variation in gene expression profiles of peripheral blood mononuclear cells from healthy volunteers. Physiol Genomics. Aug. 11,…
[cited by applicant]
Tahira K, Ueno T, Fukuda N, Aoyama T, Tsunemi A, Matsumoto S, Nagura C, Matsumoto T, Soma M, Shimba S, Matsumoto Y. Obesity alters the expression profile of clock genes in peripheral blood mononuclear cells. Arch Med Sc…
[cited by applicant]
Debey-Pascher S, Eggle D, Schultze JL: RNA stabilization of peripheral blood and profiling by bead chip analysis. Methods Mol Biol 2009, 496:175-210.
[cited by applicant]
Asare AL, Kolchinsky SA, Gao Z, Wang R, Raddassi K, Bourcier K, Seyfert-Margolis V: Differential gene expression profiles are dependent upon method of peripheral blood collection and RNA isolation. BMC Genomics 2008, 9:…
[cited by applicant]
Han MK, Swigris J, Liu L, Bartholmai B, Murray S, Giardino N, Thompson B, Frederick M, Li D, Schwarz M, Limper A, Flaherty K, Martinez FJ. Gender influences Health-Related Quality of Life in IPF. Respir Med. May 2010;10…
[cited by applicant]
Moore BB, Fry C, Zhou Y, Murray S, Han MK, Martinez FJ, Flaherty KR; The COMET Investigators. Inflammatory leukocyte phenotypes correlate with disease progression in idiopathic pulmonary fibrosis. Front Med 2014;1:56.
[cited by applicant]
De Boever P, Wens B, Forcheh AC, Reynders H, Nelen V, Kleinjans J, Van Larebeke N, Verbeke G, Valkenborg D, Schoeters G. Characterization of the peripheral blood transcriptome in a repeated measures design using a panel…
[cited by applicant]
E.L. Meaburn, C. Fernandes, I.W. Craig, R. Plomin, L.C. Schalkwyk, Assessing individual differences in genome-wide gene expression in human whole blood:reliability over four hours and stability over 10 months, Twin Res.…
[cited by applicant]
J.P. Radich, M. Mao, S. Stepaniants, M. Biery, J. Castle, T. Ward, G.Schimmack, S. Kobayashi, M. Carleton, J. Lampe, P.S. Linsley, Individual specific variation of gene expression in peripheral blood leukocytes, Genomic…
[cited by applicant]
Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, Speed TP. (2003), Summaries of Affymetrix GeneChip probe level data Nucleic Acids Research 31(4):e15 Feb. 2003.
[cited by applicant]
McCarthy, J. D, Chen, Yunshun, Smyth, K. G (2012). “Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation.”
[cited by applicant]