Luc Janss

Seniorforsker

Profile photoLuc Janss
Seniorforsker

Institut for Molekylærbiologi og Genetik
Center for Kvantitativ Genetik og Genomforskning
Blichers Allé 20
8830, Tjele
Danmark

Tlf. 87158008
Fax: 87154994
E-mail: luc.janss@agrsci.dk

Research Keywords

Statistical genetics, quantitative genetics, computational genetics, health and disease genetics, gene mapping, QTL mapping, Genome-Wide Association Studies, gene expressions, Bayesian statistics, genomic prediction, genomic selection, animal genetics, plant genetics, human genetics, multi-trait, longitudinal data, binary data, social effects, software development.

Species: human, dog, mouse, sheep, mink, cattle, pig, chicken, trout, ryegrass, wheat, barley, potato, faba bean, sweet pepper, arabidopsis, clover, rhyzobium.

Software products

Current:
Bayz: general Bayesian analysis package for variance component analysis, binary data models, Bayesian gene mapping, genomic prediction and (genomic) BLUP breeding value estimation.
Earlier packages:
MapQTL: Software for QTL mapping in plant breeding crosses, regression-based QTL mapping implementation (Kyazma, Wageningen, NL)
LDLA: Software for QTL fine-mapping by combined LD and LA mapping (based on code by Theo Meuwissen).
FlexQTL: Software for Bayesian QTL mapping in general pedigrees, mainly used in plant genetics (main developer Marco Bink, Wageningen-UR, NL).
Maggic: Software for Bayesian segregation analysis in general pedigrees.

Project funding at Aarhus University

- [new] Genomic selection without training data in winter barley, main university applicant. Industrial PhD project funded by Danish Innovation Fund, Jun 2017 – May 2020.
- [running] Breed4Biomass: Reverse breeding for biomass improvement in grasses. Co-applicant. Total budget 15.9M DKK, funded by Danish Innovation Fund Grand Solutions, Jan 2017 – Dec 2021.
- [running] NORFAB: Protein for the Northern Hemisphere (on development of faba beans as a protein crop), co-applicant. Total budget 46.4M DKK, funded by Danish Innovation Fund, Jan 2016 – Mar 2021
- [running] GreenSelect: Maximizing green grass breeding by second generation genomic selection. Main university applicant. Total budget 17.6M DKK, funded by Danish Green Development Fund, Sep 2015 – Aug 2019.
- [running] Breeding for feed efficiency and welfare for pigs in groups, co-applicant. Total budget 17.7M DKK, funded by Danish Green Development Fund, Jul 2015 – Jun 2018.
- [running] NCHAIN: Forging strong links in the organic nitrogen chain (on rhizobium-clover genetics), co-applicant. Total budget 19.4M DKK, funded by Danish Council for Strategic Research, Jan 2015 – Dec 2019.
- [running] Radimax: root deeper, produce more (on studying root-growth in 4 crops). Co-applicant. Total budget 20.7M DKK, funded by Danish High Technology Fund, Jan 2015 – Dec 2018.
- [running] GenSAP centre for genomic selection in animals and plants: co-applicant, workpackage leader / PI. Total budget 68.7M DKK, funded by Danish Innovation Fund, Jan 2013 - Dec 2018.
- [running] Genomic selection for complex traits in barley and wheat, co-applicant. Total budget 12.7M DKK, funded by Danish Green Development Fund, Oct 2013 – Sep 2017.
- [finished] ForageSelect: Genomic selection in ryegrass, co-applicant and supervisor. Total budet 15M DKK, funded by Danish Green Development Fund, Aug 2011 – Jul 2015

Teaching

- Statistical models for genomic prediction in animals and plants, Aarhus University, 1-week summer course for PhD students, main teacher, Jun 2017
- Workshop on genomic prediction tools, Ribeirao Preto, Brazil, 2-day course for MSc and PhD students, Jun 2017.
- Basics of genome wide association studies, Wuhan Agricultural University, China, 2 lectures for MSc students, Apr 2017.
- Computer intensive methods in genetic data analysis, Aarhus University, 6 days course for PhD students (course coordinator Daniel Sorensen), teaching 2 days, Sep 2016.
- Quantitative Genomics, Aarhus University, 5 ECTS MSc course on genomic prediction methods, course coordinator and main teacher, Apr – Jun 2016.
- Statistical models for genomic prediction in animals and plants, Aarhus University, 1-week summer course for PhD students, main teacher, July 2015
- Linkage and association mapping, MSc course at Aarhus University (coordinator Goutam Sahana), 1 half-day lecture, March 2015
- Quantitative Genomics, Aarhus University, 5 ECTS MSc course on genomic prediction methods, course coordinator and main teacher, Apr – Jun 2014.
- Quantitative genetics, genomics and breeding, MSc course at Copenhagen University, teaching 8 half days Nov 2013 – Jan 2014
- Linkage and association mapping, MSc course at Aarhus University (coordinator Goutam Sahana), 1 half-day lecture, March 2013
- Quantitative genetics, genomics and breeding, MSc course at Copenhagen University, teaching 4 half days Nov 2011 – Jan 2012
- Bayesian statistics for genetics and genomics, Radboud University Nijmegen Medical Centre, Netherlands, 4 half-days course for PhD’s, May 2011.
- Design and analysis of microarrays, Edinburgh, UK: 3 half days course for PhD’s, Oct 2008.
- Design and analysis of microarrays, Edinburgh, UK: 3 half days course for PhD’s, May 2006.
- Design and analysis of microarrays, Edinburgh, UK: 3 half days course for PhD’s, Dec 2005.
- Use of DNA markers in animal breeding, 1-week summer course at University of Guelph, Canada, June 2000.

Supervision

- Main supervisor for postdoc Xiangyu Guo (GreenSelect project) [current]
- Main supervisor for PhD student Marni Tausen (NCHAIN project) [current]
- Main supervisor for PhD student Charlotte Damgård Robertsen [current]
- Main AU supervisor for joint SLU-AU PhD student Berihu Welderufael [current]
- Co-supervisor for PhD student Theresa Ayirebi (GenSAP project) [current]
- Co-supervisor for PhD student Grum Gebreyesus [current]
- Co-supervisor for postdoc Nisha Shetty [current]
- Co-supervisor for PhD student Roos Zaalberg [current]
- Main supervisor for postdoc Rasmus Brøndum (GenSAP project)
- Co-supervisor for PhD student Dario Fè (ForageSelect project)
- Main AU supervisor for PhD student Setegn Alemu
- Acting as main supervisor for PhD student Lei Wang after retirement of previous supervisor
- Main supervisor for PhD student Bilal Ashraf
- Main supervisor for PhD student Alireza Ehsani
- Main supervisor for PhD student Trine Villumsen
- Co-supervisor for PhD student Tessel Galesloot (at Nijmegen University Medical Center, Netherlands)
- Co-supervisor for PhD student Burak Karacaoeren (at ETH, Zurich, Switzerland)
- Co-supervisor for PhD student Mostafa Gaderi (at ETH, Zurich, Switzerland)
- Main supervisor for postdoc Marco Bink (at Central Veterinary Institute, Lelystad, Netherlands)
- Co-supervisor for PhD student Marco Pool for one thesis-chapter (at Central Veterinary Institute, Lelystad, Netherlands)
- Co-supervisor for PhD student Mario Calus for one thesis-chapter (at Central Veterinary Institute, Lelystad, Netherlands)
- Main supervisor for Postdoc Jeanette Brandsma (at Central Veterinary Institute, Lelystad, Netherlands)
- Co-supervisor for PhD student Mirjam Nielen (based at Veterinary Faculty, Utrecht University, Netherlands)
- Co-supervisor for PhD student Marjan Van Hagen (based on Veterinary Faculty, Utrecht University, Netherlands)
- Supervisor for visiting PhD student Haja Kadarmideen (at Wageningen University, Netherlands, during postdoc)

Publication Statistics

Total peer reviewed publications*: 123
First or last author publications: 39
Total number of citations by Google Scholar: 3383
H-Index by Google Scholar: 31
*Not all are in the list below due to missing publication from earlier employment

Publikationer

Breeding for dual-purpose wheat varieties using marker–trait associations for biomass yield and quality traits

Malik, P. L., Janss, L., Nielsen, L. K., Borum, F., Jørgensen, H., Eriksen, B., Schjoerring, J. K. & Rasmussen, S. K., dec. 2019, I : Theoretical and Applied Genetics. 132, 12, s. 3375-3398 24 s.

Multi-Trait and Trait-Assisted Genomic Prediction of Winter Wheat Quality Traits Using Advanced Lines from Four Breeding Cycles

Kristensen, P. S., Jahoor, A., Andersen, J. R., Jihad, O., Janss, L. & Jensen, J., aug. 2019, I : Hapres CBGG; Crop, Breeding, Genetics, Genomics. :e190010.

Models with indirect genetic effects depending on group sizes: a simulation study assessing the precision of the estimates of the dilution parameter

Heidaritabar, M., Bijma, P., Janss, L., Bortoluzzi, C., Nielsen, H. M., Madsen, P., Ask, B. & Christensen, O. F., maj 2019, I : Genetics Selection Evolution. 51, 1, s. 24 10 s., 24.

Improving genomic predictions by correction of genotypes from genotyping by sequencing in livestock populations

Wang, X., Lund, M. S., Ma, P., Janss, L., Kadarmideen, H. N. & Su, G., 24 jan. 2019, I : Journal of Animal Science and Biotechnology. 10, 8.

Genetic analysis of Fourier transform infrared milk spectra in Danish Holstein and Danish Jersey

Zaalberg, R. M., Shetty, N., Janss, L. & Buitenhuis, A. J., jan. 2019, I : Journal of Dairy Science. 102, 1, s. 503-510 8 s.

Genomic Prediction Using Multi-trait Weighted GBLUP Accounting for Heterogeneous Variances and Covariances Across the Genome

Karaman, E., Lund, M. S., Anche, M. T., Janss, L. & Su, G., 6 nov. 2018, I : G3: Genes, Genomes, Genetics (Bethesda). 8, 11, s. 3549-3558 10 s.

The value of expanding the training population to improve genomic selection models in tetraploid potato

Sverrisdóttir, E., Sundmark, E. H. R., Johnsen, H. Ø., Kirk, H. G., Asp, T., Janss, L., Bryan, G. & Nielsen, K. L., 6 aug. 2018, I : Frontiers in Plant Science. 9, 14 s., 1118.

Genome-wide association study for susceptibility to and recoverability from mastitis in Danish Holstein cows

Welderufael, B. G., Løvendahl, P., De Koning, D-J., Janss, L. & Fikse, F., 24 apr. 2018, I : Frontiers in Genetics. 9, 12 s., 141.

Optimized Use of Low-Depth Genotyping-by-Sequencing for Genomic Prediction among multi-parental Family Pools and Single Plants in Perennial Ryegrass (Lolium perenne L.)

Cericola, F., Lenk, I., Fè, D., Byrne, S., Jensen, C. S., Pedersen, M. G., Asp, T., Jensen, J. & Janss, L., mar. 2018, I : Frontiers in Plant Science. 9, 12 s., 369.

Genome-wide association studies and comparison of models and cross-validation strategies for genomic prediction of quality traits in advanced winter wheat breeding lines

Kristensen, P. S., Jahoor, A., Andersen, J. R., Cericola, F., Orabi, J., Janss, L. L. & Jensen, J., 2 feb. 2018, I : Frontiers in Plant Science. 9, 15 s., 69.

Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits

Gebreyesus, G., Lund, M. S., Buitenhuis, A. J., Bovenhuis, H., Poulsen, N. A. & Janss, L., 5 dec. 2017, I : Genetics Selection Evolution. 49, 13 s., 89.

Can we validate the results of twin studies? A census-based study on the heritability of educational achievement

Schwabe, I., Janss, L. & van den Berg, S. M., 26 okt. 2017, I : Frontiers in Genetics. 8, 8 s., 160.

Genomic prediction of starch content and chipping quality in tetraploid potato using genotyping-by-sequencing

Sverrisdóttir, E., Byrne, S., Sundmark, E. H. R., Johnsen, H. Ø., Kirk, H. G., Asp, T., Janss, L. & Nielsen, K. L., 13 jul. 2017, I : Theoretical and Applied Genetics. 130, 10, s. 2091-2108 18 s.

Bivariate threshold models for genetic evaluation of susceptibility to and ability to recover from mastitis in Danish Holstein cows

Welderufael, B. G., Janss, L. L. G., de Koning, D. J., Sørensen, L. P., Løvendahl, P. & Fikse, W. F., 1 jun. 2017, I : Journal of Dairy Science. 100, 6, s. 4706-4720 15 s.

The patterns of genomic variances and covariances across genome for milk production traits between Chinese and Nordic Holstein populations

Li, X., Lund, M. S., Janss, L., Wang, C., Ding, X., Zhang, Q. & Su, G., 15 mar. 2017, I : BMC Genetics. 18, 12 s., 26.

Simultaneous genetic evaluation of simulated mastitis susceptibility and recovery ability using a bivariate threshold sire model

Welderufael, B. G., de Koning, D. J., Janss, L. L. G., Franzén, J. & Fikse, W. F., 17 jan. 2017, I : Acta Agriculturae Scandinavica, Section A - Animal Science. 66, 3, s. 125-134 10 s.

Optimizing Training Population Size and Genotyping Strategy for Genomic Prediction Using Association Study Results and Pedigree Information. A Case of Study in Advanced Wheat Breeding Lines

Cericola, F., Jahoor, A., Orabi, J., Andersen, J. R., Janss, L. L. & Jensen, J., 2017, I : P L o S One. 12, 1, s. e0169606

Accuracy of genomic prediction in a commercial perennial ryegrass breeding program

Fè, D., Ashraf, B. H., Pedersen, M. G., Janss, L., Byrne, S., Roulund, N., Lenk, I., Didion, T., Asp, T., Jensen, C. S. & Jensen, J., 1 nov. 2016, I : Plant Genome. 9, 3, 12 s.

Genome-wide association analyses using a Bayesian approach for litter size and piglet mortality in Danish Landrace and Yorkshire pigs

Guo, X., Su, G., Christensen, O. F., Janss, L. & Lund, M. S., 18 jun. 2016, I : BMC Genomics. 17, 12 s., 468.

Genomic prediction using phenotypes from pedigreed lines with no marker data

Ashraf, B., Edriss, V., Akdemir, D., Autrique, E., Bonnett, D., Crossa, J., Janss, L., Singh, R. & Jannink, J. L., 1 maj 2016, I : Crop Science. 56, 3, s. 957-964 8 s.

Short communication: Multi-trait estimation of genetic parameters for milk protein composition in the Danish Holstein

Gebreyesus, G., Lund, M. S., Janss, L., Poulsen, N. A., Larsen, L. B., Bovenhuis, H. & Buitenhuis, A. J., 21 jan. 2016, I : Journal of Dairy Science. 99, 4, s. 2863-2866 4 s.

Estimating genomic heritabilities at the level of family-pool samples of perennial ryegrass using genotyping-by-sequencing

Ashraf, B. H., Byrne, S., Fé, D., Czaban, A., Asp, T., Pedersen, M. G., Lenk, I., Roulund, N., Didion, T., Jensen, C. S., Jensen, J. & Janss, L. L., jan. 2016, I : Theoretical and Applied Genetics. 129, 1, s. 45-52 8 s.

Decomposing genomic variances in a mouse F2 population using information from GWA, GWE and eQTL analyses

Ehsani, A., Janss, L., Pomp, D. & Sørensen, P., 2016, I : Animal Genetics. 47, 2, s. 165-173 9 s.

Estimation of indirect genetic effects in group-housed mink (Neovison vison) should account for systematic interactions either due to kin or sex

Alemu, S. W., Berg, P., Janss, L. & Bijma, P., 2016, I : Journal of Animal Breeding and Genetics. 133, 1, s. 43-50 8 s.

Genomic prediction of growth in pigs based on a model including additive and dominance effects

Lopes, M. S., Bastiaansen, J. W. M., Janss, L., Knol, E. F. & Bovenhuis, H., 2016, I : Journal of Animal Breeding and Genetics (Online). 133, 3, s. 180-186 7 s.

Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data

Lopes, M. S., Bastiaansen, J. W. M., Janss, L., Knol, E. F. & Bovenhuis, H., 1 dec. 2015, I : G3: Genes, Genomes, Genetics (Bethesda). 5, 12, s. 2629-2637 8 s.

Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction

Brøndum, R. F., Su, G., Janss, L., Sahana, G., Guldbrandtsen, B., Boichard, D. A. & Lund, M. S., jun. 2015, I : Journal of Dairy Science. 98, 6, s. 4107-4116 10 s.

SNP annotation-based whole genomic prediction and selection: an application to feed efficiency and its component traits in pigs

Do, D. N., Janss, L., Jensen, J. & Kadarmideen, H. N., maj 2015, I : Journal of Animal Science. 93, 5, s. 2056-2063 8 s.

Estimation of heritability of different outcomes for genetic studies of TNFi response in patients with rheumatoid arthritis

Umićević Mirkov, M., Janss, L., Vermeulen, S. H., van de Laar, M. A. F. J., van Riel, P. L. C. M., Guchelaar, H-J., Brunner, H. G., Albers, C. A. & Coenen, M. J. H., 2015, I : Annals of the Rheumatic Diseases. 74, 12, s. 2183-2187 5 s.

Genome-wide association study reveals novel loci for litter size and its variability in a Large White pig population

Sell-Kubiak, E., Duijvesteijn, N., Lopes, M. S., Janss, L. L. G., Knol, E. F., Bijma, P. & Mulder, H. A., 2015, I : BMC Genomics. 16, 1049.

Genomic dissection and prediction of heading date in perennial ryegrass

Fè, D., Cericola, F., Byrne, S., Lenk, I., Ashraf, B. H., Pedersen, M. G., Roulund, N., Asp, T., Janss, L., Jensen, C. S. & Jensen, J., 2015, I : B M C Genomics. 16, 921, s. 1-15 16 s.

Iron and hepcidin as risk factors in atherosclerosis: what do the genes say?

Galesloot, T. E., Janss, L. L., Burgess, S., Kiemeney, L. A. L. M., den Heijer, M., de Graaf, J., Holewijn, S., Benyamin, B., Whitfield, J. B., Swinkels, D. W. & Vermeulen, S. H., 2015, I : BMC Genetics. 16, s. 1-12 13 s., 79.

Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle

Buitenhuis, B., Janss, L. L. G., Poulsen, N. A., Larsen, L. B., Larsen, M. K. & Sørensen, P., 15 dec. 2014, I : B M C Genomics. 15, 1112, s. 1-11 11 s.

Comparison of genomic predictions using genomic relationship matrices built with different weighting factors to account for locus-specific variances

Su, G., Christensen, O. F., Janss, L. & Lund, M. S., okt. 2014, I : Journal of Dairy Science. 97, 10, s. 6547-6559 13 s.

Combining SNPs in latent variables to improve genomic prediction

Heuven, H. C. M., Rosa, G. J. M. & Janss, L., 17 aug. 2014. 3 s.

Disentangling Pleiotropy along the Genome using Sparse Latent Variable Models

Janss, L., 17 aug. 2014. 4 s.

Evaluation of Antedependence Model Performance and Genomic Prediction for Growth in Danish Pigs

Wang, L., Edwards, D. & Janss, L., 17 aug. 2014. 3 s.

Genetic Analysis of Daily Maximum Milking Speed by a Random Walk Model in Dairy Cows

Karacaören, B., Janss, L. & Kadarmideen, H., 17 aug. 2014. 3 s.

Genetic Architecture of Milk, Fat, Protein, Mastitis and Fertility Studied using NGS Data in Holstein Cattle

Sahana, G., Janss, L., Guldbrandtsen, B. & Lund, M. S., 17 aug. 2014. 3 s.

Genetic and non-genetic indirect effects for bite mark traits in group housed mink

Alemu, S. W., Berg, P., Janss, L., Møller, S. H. & Bijma, P., 17 aug. 2014. 3 s.

Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models

Do, D. N., Janss, L. L. G., Strathe, A. B. & Kadarmideen, H. N., 17 aug. 2014. 3 s.

Genomic prediction using QTL derived from whole genome sequence data

Brøndum, R. F., Su, G., Janss, L., Sahana, G. & Lund, M. S., 17 aug. 2014. 3 s.

Longitudinal Analysis of Somatic Cell Count for Joint Genetic Evaluation of Mastitis and Recovery Liability

Welderufael, B. G., de Koning, D. J., Janss, L., Franzén, J. & Fikse, W. F., 17 aug. 2014. 3 s.

Using SNP markers to estimate additive, dominance and imprinting genetic variance

Lopes, M. S., Bastiaansen, J. W. M., Janss, L., Bovenhuis, H. & Knol, E. F., 17 aug. 2014. 3 s.

Whole-Genome Analyses of lung function, height and smoking

Janss, L., Sigsgaard, T. & Sorensen, D., 1 aug. 2014, I : Annals of Human Genetics. 78, 6, s. 452-467 12 s.

Association studies using family pools of outcrossing crops based on allele-frequency estimates from DNA sequencing

Ashraf, B., Jensen, J., Asp, T. & Janss, L., 1 jun. 2014, I : Theoretical and Applied Genetics. 127, 6, s. 1331-1341 11 s.

A comparison of multivariate genome-wide association methods

Galesloot, T. E., Van Steen, K., Kiemeney, L. A. L. M., Janss, L. L. & Vermeulen, S. H., 24 apr. 2014, I : P L o S One. 9, 4, s. 1-8 8 s., e95923.

Exploring causal networks of bovine milk fatty acids in a multivariate mixed model context

Bouwman, A. C., Valente, B. D., Janss, L. L. G., Bovenhuis, H. & Rosa, G. J. M., 17 jan. 2014, I : Genetics Selection Evolution. 46, 2, s. 1-2 12 s.

Indirect genetic effects and kin recognition: estimationg IGEs wehn interactions differ between kin and strangers

Alemu, S. W., Berg, P., Janss, L. & Bijma, P., jan. 2014, I : Heredity. 112, s. 197-206 10 s.

Indirect genetic effects contribute substantially to heritable variation in aggression-related traits in group-housed mink (Neovison vison)

Alemu, S. W., Bijma, P., Møller, S. H., Janss, L. & Berg, P., 2014, I : Genetics Selection Evolution. 46, 30

Genome-wide and local pattern of linkage disequilibrium and persistence of phase for 3 Danish pig breeds

Wang, L., Sørensen, P., Janss, L., Ostersen, T. & Edwards, D., 5 dec. 2013, I : BMC Genetics. 14, 115, 11 s.

Model comparison on genomic predictions using high-density markers for different groups of bulls in the Nordic Holstein population: (submitted 2012)

Gao, H., Su, G., Janss, L., Yuan, Z. & Lund, M. S., jun. 2013, I : Journal of Dairy Science. 96, 7, s. 4678-4687 10 s.

SNP based heritability estimation using a Bayesian approach

Krag, K., Janss, L., Mahdi Shariati, M., Berg, P. & Buitenhuis, A. J., apr. 2013, I : Animal. 7, 4, s. 531-539 9 s.

Inferring genetic architecture of complex traits using Bayesian integrative analysis of genome and transcriptiome data

Ehsani, A., Sørensen, P., Pomp, D., Allan, M. & Janss, L., 5 sep. 2012, I : B M C Genomics. 13, 456, s. 1-9 9 s.

Estimation of (co)variances for genomic regions of flexible sizes: application to complex infectious udder diseases in dairy cattle

Sørensen, L. P., Janss, L., Madsen, P., Mark, T. & Lund, M. S., 6 jul. 2012, I : Genetics Selection Evolution. 44, 18, s. 1-15 15 s.

Efficiency of genomic selection using Bayesian multimarker models for traits selected to reflect a wide range of heritabilities and frequencies of detected quantitative traits loci in mice

Kapell, D. NRG., Sorensen, D., Su, G., Janss, L., Ashworth, C. J. & Roehe, R., 31 maj 2012, I : B M C Genetics. 13, 42

A two step Bayesian approach for genomic prediction of breeding values

Mahdi Shariati, M., Sørensen, P. & Janss, L., 21 maj 2012, I : BMC Proceedings. 6, (Suppl 2):S12 , 5 s.

A Bayesian variable selection procedure for ranking overlapping gene sets

Skarman, A., Mahdi Shariati, M., Janss, L., Jiang, L. & Sørensen, P., 3 maj 2012, I : B M C Bioinformatics. 13, 73, s. 1-9 9 s.

Current self-reported symptoms of attention deficit/hyperactivity disorder are associated with total brain volume in healthy adults

Hoogman, M., Rijpkema, M., Janss, L., Brunner, H., Fernandez, G., Buitelaar, J., Franke, B. & Arias-Vásquez, A., 10 feb. 2012, I : P L o S One. 7, 2, s. e31273 4 s.

Inferences from Genomic Models in Stratified Populations

Janss, L., de los Campos, G., Sheehan, N. & Sorensen, D., 2012, I : Genetics (Online). 192, 2, s. 693-704 9 s.

Predicting Breeding Values in Animals by Kalman Filter: Application to Body Condition Scores in Dairy Cattle

Karacaoren, B., Janss, L. L. G. & Kadarmideen, H. N., 2012, I : Kafkas Universitesi Veteriner Fakultesi Dergisi. 18, 4, s. 627-632

Bayesian multi-QTL mapping for growth curve parameters

Heuven, H. C. M. & Janss, L. L. G., 2010, I : BMC Proceedings. 1, 6 s.

Comparison of association mapping methods in a complex pedigreed population

Sahana, G., Guldbrandtsen, B., Janss, L. & Lund, M. S., 2010, I : Genetic Epidemiology. 34, 5, s. 455-462 8 s.

Heterogeneity of Genetic Modifiers Ensures Normal Cardiac Development

Winston, J. B., Erlich, J. M., Green, C. A., Aluko, A., Kaiser, K. A., Takematsu, M., Barlow, R. S., Sureka, A. O., LaPage, M. J., Janss, L. & Jay, P. Y., 2010, I : Circulation Journal. 121, 11, s. 1313-1321 9 s.

Relationship of cryptorchidism with sex ratios and litter sizes in 12 dog breeds

Gubbels, E. J., Scholten, J., Janss, L. & Rothuizen, J., jul. 2009, I : Animal Reproduction Science. 113, 1-4, s. 187-195 9 s.

Bayesian genomic selection: the effect of haplotype length and priors

Villumsen, T. M. & Janss, L., feb. 2009, I : BMC Proceedings. 3(Suppl 1), s. 11

Bayesian genomic selection: the effect of haplotype lenghts and priors

Villumsen, T. M. & Janss, L., 2009, I : BMC Proceedings. (Supp 1):S11, 5 s.

Differentially Expressed Genes for Aggressive Pecking Behaviour in Laying Hens

Buitenhuis, B., Hedegaard, J., Janss, L. & Sorensen, P., 2009, I : B M C Genomics. 10, 544, 31 s.

Evidence of major genes affecting stress response in rainbow trout using Bayesian methods of complex segregation analysis

Vallejo, R. L., Rexroad III, C. E., Silverstein, J. T., Janss, L. & Weber, G. M., 2009, I : Journal of Animal Science. 87, 11, s. 3490-3505 15 s.

The importance of haplotype lenght and heritability using genomic selection in dairy cattle

Villumsen, T. M., Janss, L. & Lund, M. S., 2009, I : Journal of Animal Breeding and Genetics. 126, 1, s. 3-13 10 s.

Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes

Jaffrézic, F., de Koning, D-J., Boettcher, P. J., Bonnet, A., Buitenhuis, B., Closset, R., Déjean, S., Delmas, C., Detilleux, J. C., Dove, P., Duval, M., Foulley, J-L., Hedegaard, J., Hornshøj, H., Hulsegge, I. B., Janss, L., Jensen, K., Jiang, L., Lavric, M., Lê Cao, K-A., Lund, M. S., Malinverni, R., Marot, G., Nie, H., Petzl, W., Pool, M. H., Robert-Granié, C., San Christobal, M., van Schothorst, E. M., Schuberth, H-J., Sørensen, P., Stella, A., Tosser-Klopp, G., Waddington, D., Watson, M., Yang, W., Zerbe, H. & Seyfert, H-M., 2007, I : Genetics Selection Evolution. 39, s. 633-650 13 s.

The EADGENE Microarray Data Analysis Workshop

de Koning, D-J., Jaffrézic, F., Lund, M. S., Watson, M., Channing, C., Hulsegge, I., Pool, M., Buitenhuis, B., Hedegaard, J., Hornshøj, H., Jiang, L., Sørensen, P., Marot, G., Delmas, C., Lê Cao, K-A., SanChristobal, M., Baron, M. D., Malinverni, R., Stella, A., Brunner, R., Seyfert, H-M., Jensen, K., Mouzaki, D., Waddington, D., Jiménez-Martin, A., Alegre, M. P., Pérez, E., Closset, R., Detilleux, J., Dovc, P., Lavric, M. & Janss, L., 2007, I : Genetics Selection Evolution. 39, s. 621-631 11 s.

Investigation of major gene for milk yield, milking speed, dry matter intake, and body weight in dairy cattle

Karacaören, B., Kadarmideen, H. & Janss, L. L. G., 2006, I : Journal of Applied Genetics. 47, 4, s. 337-43 7 s.

Detection of quantitative trait loci for backfat thickness and intramuscular fat content in pigs (Sus scrofa)

de Koning, D-J., Janss, L. LG., Rattink, A. P., van Oers, P. AM., de Vries, B. J., Groenen, M. AM., van der Poel, J. J., de Groot, P. N., Brascamp, EW. & van Arendonk, J. AM., 1999, I : Genetics. 152, 4, s. 1679-1690 12 s.

MCMC based estimation of variance components in a very large dairy cattle data set

Janss, L. & de Jong, G., 1999, I : Interbull Bulletin. s. 63 1 s.

Bayesian statistical analyses for presence of single genes affecting meat quality traits in a crossed pig population

Janss, LLG., Van Arendonk, JAM. & Brascamp, EW., 1997, I : Genetics. 145, 2, s. 395-408 14 s.

Segregation analyses for presence of major genes affecting growth, backfat, and litter size in Dutch Meishan crossbreds.

Janss, LL., Van Arendonk, JA. & Brascamp, EW., 1997, I : Journal of animal science. 75, 11, s. 2864-2876 13 s.

Estimation of direct and maternal genetic (co) variances for survival within litters of piglets

van Arendonk, J. AM., van Rosmeulen, C., Janss, L. LG. & Knol, E. F., 1996, I : Livestock Production Science. 46, 3, s. 163-171 9 s.

Application of Gibbs sampling for inference in a mixed major gene-polygenic inheritance model in animal populations

Janss, LLG., Thompson, R. & Van Arendonk, JAM., 1995, I : Theoretical and Applied Genetics. 91, 6-7, s. 1137-1147 11 s.

Computing approximate monogenic model likelihoods in large pedigrees with loops

Janss, LLG., Arendonk, JAM. V. & Van der Werf, JHJ., 1995, I : Genetics Selection Evolution. 27, 6, s. 1-13 13 s.

A note on the estimation of the effective number of additive and dominant loci contributing to quantitative variation.

Ollivier, L. & Janss, LL., 1993, I : Genetics. 135, 3, s. 907-909 3 s.

Bivariate analysis for one continuous and one threshold dichotomous trait with unequal design matrices and an application to birth weight and calving difficulty

Janss, LLG. & Foulley, J-L., 1993, I : Livestock Production Science. 33, 3-4, s. 183-198 16 s.

Effect of divergent selection for immune responsiveness and of major histocompatibility complex on resistance to Marek’s disease in chickens

Pinard, M-H., Janss, LLG., Maatman, R., Noordhuizen, JPTM. & Van der Zijpp, AJ., 1993, I : Poultry Science. 72, 3, s. 391-402 12 s.

Identification of a major gene in F 1 and F 2 data when alleles are assumed fixed in the parental lines

Janss, LLG. & Van Der Werf, JHJ., 1992, I : Genetics Selection Evolution. 24, 6, s. 511 1 s.