Multi-omic data integration

December 20, 2022

  1. rpl: Randomized pairwise likelihood method for complex statistical inferences πŸ”—
  2. padma: Pathway deviation scores using multiple factor analysis πŸ”—
  3. Regeneration Rosetta: An R/Shiny interactive web application to explore regeneration-associated gene expression and chromatin accessibility πŸ”—
  4. maskmeans: Multi-view aggregation/splitting K-means clustering algorithm πŸ”—
  5. Edge in TCGA: An R/Shiny interactive web application for the exploration of drivers of gene expression in The Cancer Genome Atlas πŸ”—

  1. Mollandin, F., Gilbert, H., Croiseau, P., and Rau, A. (2022) Accounting for overlapping annotations in genomic prediction models of complex traits. BMC Bioinformatics, 23:65. πŸ”— πŸ“„ πŸ”„ πŸ’»

  2. Mollandin, F., Gilbert, H., Croiseau, P., and Rau, A. (2022) Capitalizing on complex annotations in Bayesian genomic prediction for a backcross population of growing pigs. 12th World Congress on Genetics Applied to Livestock Production (3-8 July 2022), Rotterdam, Netherlands.

  3. Rau, A., Manansala, R., Flister, M. J., Rui, H., JaffrΓ©zic, F., LaloΓ«, D., and Auer, P. L. (2022) Individualized multi-omic pathway deviation scores using multiple factor analysis. Biostatistics, 23(2):362-379. πŸ”— πŸ“„ πŸ”„ πŸ”’ πŸ’»

  4. Mazo, G., Karlis, D., and Rau, A. (2022) A randomized pairwise likelihood method for complex statistical inferences. NA, Submitted. πŸ”„ πŸ’»

  5. Godichon-Baggioni, A., Maugis-Rabusseau, C. and Rau, A. (2020) Multi-view cluster aggregation and splitting, with an application to multi-omic breast cancer data. Annals of Applied Statistics, 14:2, 752-767. πŸ”— πŸ“„ πŸ”’

  6. Foissac, S., Djebali, S., Munyard, K., Villa-Vialaneix, N., Rau, A., Muret, K., Esquerre, D., Zytnicki, M., Derrien, T., Bardou, P., Blanc, F., Cabau, C., Crisci, E., Dhorne-Pollet, S., Drouet, F., Gonzales, I., Goubil, A., Lacroix-Lamande, S., Laurent, F., Marthey, S., Marti-Marimon, M., Momal-Leisenring, R., Mompart, F., Quere, P., Robelin, D., San Cristobal, M., Tosser-Klopp, G., Vincent-Naulleau, S., Fabre, S., Pinard-Van der Laan, M.-H., Klopp, C., Tixier-Boichard, M., Acloque, H., Lagarrigue, S., Giuffra, E. (2019) Multi-species annotation of transcriptome and chromatin structure in domesticated animals. BMC Biology, 18:48. πŸ”— πŸ“„ πŸ”„

  7. Dhara, S., Rau, A., Flister, M., Recka, N., Laiosa, M., Auer, P., and Udvadia, A. (2019) Cellular reprogramming for successful CNS axon regeneration is driven by a temporally changing cast of transcription factors. Scientific Reports, 9:14198. πŸ”— πŸ“„ πŸ”„ πŸ”’

  8. Rau, A., Dhara, S., Udvadia, A., and Auer, P. (2019) Regeneration Rosetta: An interactive web application to explore regeneration-associated gene expression and chromatin accessibility. G3: Genes|Genomes|Genetics, 9(12): 3953-3959. πŸ”— πŸ“„ πŸ”’

  9. Rau, A., Flister, M. J., Rui, H. and Livermore Auer, P. (2019) Exploring drivers of gene expression in The Cancer Genome Atlas. Bioinformatics, 35(1): 62-68. πŸ”— πŸ“„ πŸ”„ πŸ”’

Posted on:
December 20, 2022
Length:
2 minute read, 410 words
Categories:
projects
Tags:
hugo-site
See Also:
RNA-seq co-expression
Outreach
Network inference