Hi Ricardo, It works for me from my desktop machine behind the strong network of the University. And it also fails from my laptop at home. Maybe it comes from GitHub and our way to connect overthere. I do not know.
--8<---------------cut here---------------start------------->8--- $ guix import cran -a git https://github.com/RubD/Giotto/ -r Starting download of /tmp/guix-file.wKIOEz >From http://cran.r-project.org/src/contrib/dbscan_1.1-10.tar.gz... …-10.tar.gz 2.2MiB 3.6MiB/s 00:01 [##################] 100.0% Starting download of /tmp/guix-file.zTh09D >From >https://bioconductor.org/packages/release/bioc/src/contrib/lfa_1.24.0.tar.gz... ….0.tar.gz 284KiB 46.9MiB/s 00:00 [##################] 100.0% Starting download of /tmp/guix-file.wx30kh >From >https://bioconductor.org/packages/release/bioc/src/contrib/lfa_1.24.0.tar.gz... ….0.tar.gz 284KiB 55.6MiB/s 00:00 [##################] 100.0% (define-public r-lfa (package (name "r-lfa") (version "1.24.0") (source (origin (method url-fetch) (uri (bioconductor-uri "lfa" version)) (sha256 (base32 "02b90xjb2lfm86hbsdrvzpv20pijnq78ibz4dwjzqd9v4xhia3wr")))) (properties `((upstream-name . "lfa"))) (build-system r-build-system) (propagated-inputs (list r-corpcor)) (native-inputs (list r-knitr)) (home-page "https://github.com/StoreyLab/lfa";) (synopsis "Logistic Factor Analysis for Categorical Data") (description "LFA is a method for a PCA analogue on Binomial data via estimation of latent structure in the natural parameter.") (license gpl3))) (define-public r-dbscan (package (name "r-dbscan") (version "1.1-10") (source (origin (method url-fetch) (uri (cran-uri "dbscan" version)) (sha256 (base32 "1h8x1v9kk5zmw5qd575cyr16yz8l226lsaq71n079l4i8crcrzg1")))) (properties `((upstream-name . "dbscan"))) (build-system r-build-system) (propagated-inputs (list r-rcpp)) (native-inputs (list r-knitr)) (home-page "https://github.com/mhahsler/dbscan";) (synopsis "Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Related Algorithms") (description "This package provides a fast reimplementation of several density-based algorithms of the DBSCAN family. Includes the clustering algorithms DBSCAN (density-based spatial clustering of applications with noise) and HDBSCAN (hierarchical DBSCAN), the ordering algorithm OPTICS (ordering points to identify the clustering structure), shared nearest neighbor clustering, and the outlier detection algorithms LOF (local outlier factor) and GLOSH (global-local outlier score from hierarchies). The implementations use the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided. Hahsler, Piekenbrock and Doran (2019) <doi:10.18637/jss.v091.i01>.") (license gpl2+))) (define-public r-giotto (let ((commit "68d7390dce87223cac11d4d8f31705fe0144d011") (revision "1")) (package (name "r-giotto") (version (git-version "1.1.1" revision commit)) (source (origin (method git-fetch) (uri (git-reference (url "https://github.com/RubD/Giotto/";) (commit commit))) (file-name (git-file-name name version)) (sha256 (base32 "0mv60khc05wrxzr4ir6cirn7dpqvgwan5hm00lmafsyalr51nf5i")))) (properties `((upstream-name . "Giotto"))) (build-system r-build-system) (propagated-inputs (list r-clusterr r-complexheatmap r-cowplot r-data-table r-dbscan r-deldir r-farver r-fitdistrplus r-ggdendro r-ggplot2 r-ggraph r-ggrepel r-igraph r-irlba r-lfa r-limma r-magick r-magrittr r-matrix r-matrixstats r-plotly r-qvalue r-r-utils r-rcolorbrewer r-rcpp r-reshape2 r-reticulate r-rfast r-rlang r-rtsne r-scales r-uwot)) (native-inputs (list r-knitr)) (home-page "https://github.com/RubD/Giotto/";) (synopsis "Spatial Single-Cell Transcriptomics Toolbox") (description "Toolbox to process, analyze and visualize spatial single-cell expression data.") (license #f)))) --8<---------------cut here---------------end--------------->8--- Cheers, simon
