Google Scholar

A complete list of publications is available from Google Scholar.


  • Righell D.*, Weber L.M.*, Crowell H.L.*, Pardo B., Collado-Torres L., Ghazanfar S., Lun A.T.L., Hicks S.C.+, and Risso D.+ (2021), SpatialExperiment: infrastructure for spatially resolved transcriptomics data in R using Bioconductor, bioRxiv. Paper, R/Bioconductor package.

  • Tippani M., Divecha H.R., Catallini II J.L., Weber L.M., Spangler A., Jaffe A.E., Hicks S.C., Martinowich K., Collado-Torres L., Page S.C., and Maynard K.R. (2021), VistoSeg: a MATLAB pipeline to process, analyze and visualize high-resolution histology images for Visium spatial transcriptomics data, bioRxiv. Paper, Software, Code.

  • Pardo B., Spangler A., Weber L.M., Hicks S.C., Jaffe A.E., Martinowich K., Maynard K.R., and Collado-Torres L. (2021), spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data, bioRxiv. Paper, R/Bioconductor package.

  • Tiberi S., Crowell H.L., Weber L.M., Samartsidis P., and Robinson M.D. (2021), distinct: a novel approach to differential distribution analyses, bioRxiv. Paper, R/Bioconductor package.

  • Petrillo M., Fabbri M., Kagkli D.M. et al. (2021), A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing, F1000Research, v1, 10:80. Paper.

  • Krieg C., Carloni S., Weber L.M., Fosso B., Hardiman G., Mileti E., El Aidy S., Marzano M., Pesole G., Asnicar F., Segata N., Robinson M.D., and Guglietta S. (2021), Loss of C3aR induces immune infiltration and inflammatory microbiota in a new spontaneous model of colon cancer, bioRxiv. Paper.

Published papers

  • Weber L.M., Hippen A.A., Hickey P.F., Berrett K.C., Gertz J., Doherty J.A., Greene C.S., and Hicks S.C. (2021), Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design, GigaScience, 10, 9, giab062. Paper, Code, Data, Data (controlled access).

  • Liechti T., Weber L.M., Ashhurst T.M., Stanley N., Prlic M., Van Gassen S., and Mair F. (2021), An updated guide for the perplexed: cytometry in the high-dimensional era, Nature Immunology. Paper.

  • Hippen A.A., Falco M.M., Weber L.M., Erkan E.P., Zhang K., Doherty J.A., Vähärautio A., Greene C.S., and Hicks S.C. (2021), miQC: An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data, PLOS Computational Biology. Paper, R/Bioconductor package.

  • Maynard K.R.*, Collado-Torres L.*, Weber L.M., Uytingco C., Barry B.K., Williams S.R., Catallini J.L. II, Tran M.N., Besich Z., Tippani M., Chew J., Yin Y., Kleinman J.E., Hyde T.M., Rao N., Hicks S.C., Martinowich K.+, Jaffe A.E.+ (2021), Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex, Nature Neuroscience, 24, 425-436. Paper, Web application, R/Bioconductor package, Code for paper, Code for web application.

  • Shaul M.E., Eyal O., Guglietta S., Aloni P., Zlotnik A., Forkosh E., Levy L., Weber L.M., Levin Y., Pomerantz A., Nechushtan H., Eruslanov E., Singhal S., Robinson M.D., Krieg C., and Fridlender Z.G. (2020), Circulating neutrophil subsets in advanced lung cancer patients exhibit unique immune signature and relate to prognosis, FASEB Journal, 34, 3, 4204–4218. Paper.

  • Weber L.M., Saelens W., Cannoodt R., Soneson C., Hapfelmeier A., Gardner P.P., Boulesteix A.-L., Saeys Y., and Robinson M.D. (2019), Essential guidelines for computational method benchmarking, Genome Biology, 20, 125. Paper.

  • Weber L.M. and Soneson C. (2019), HDCytoData: Collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats, F1000Research, 8:1459, v2. Paper, R/Bioconductor package.

  • Weber L.M., Nowicka N., Soneson C., and Robinson M.D. (2019), diffcyt: Differential discovery in high-dimensional cytometry via high-resolution clustering, Communications Biology, 2, 183. Paper, R/Bioconductor package, Code, Data.

  • Krieg C., Nowicka M., Guglietta S., Schindler S., Hartmann F.J., Weber L.M., Dummer R., Robinson M.D., Levesque M.P.* and Becher B.* (2018), High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy, Nature Medicine, 24, 2, 144–153. Paper.

  • Nowicka N., Krieg C., Crowell H.L., Weber L.M., Hartmann F.J., Guglietta S., Becher B., Levesque M.P., and Robinson M.D. (2017; updated 2019), CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets, F1000Research, 6:748, v3. Paper, R/Bioconductor package.

  • Weber L.M. and Robinson M.D. (2016), Comparison of clustering methods for high‐dimensional single‐cell flow and mass cytometry data, Cytometry Part A, 89A, 12, 1084–1096. Paper, Code, Data.

  • Hartmann F.J., Bernard-Valnet R., Quériault C., Mrdjen D., Weber L.M., Galli E., Krieg C., Robinson M.D., Nguyen X.-H., Dauvilliers Y., Liblau R.S., and Becher B. (2016), High-dimensional single-cell analysis reveals the immune signature of narcolepsy, Journal of Experimental Medicine, 213, 12, 2621–2633. Paper.

  • Burger A.*, Lindsay H.*, Felker A., Hess C., Anders C., Chiavacci E., Zaugg J., Weber L.M., Catena R., Jinek M., Robinson M.D., and Mosimann C. (2016), Maximizing mutagenesis with solubilized CRISPR-Cas9 ribonucleoprotein complexes, Development, 143, 2025–2037. Paper.

  • Robinson M.D., Kahraman A., Law C.W., Lindsay H., Nowicka M., Weber L.M., and Zhou X. (2014), Statistical methods for detecting differentially methylated loci and regions, Frontiers in Genetics, 5, 324. Paper.