| import sys | |
| from IPython.core.magic import register_cell_magic | |
| from IPython.display import Javascript | |
| import IPython | |
| @register_cell_magic | |
| def antigravity(line, cell): | |
| """Invokes Google Antigravity CLI to rewrite the current cell based on a prompt.""" | |
| import subprocess | |
| import json |
| FROM us.gcr.io/broad-dsp-gcr-public/terra-base:1.0.1 | |
| USER root | |
| # utilities for Bioconductor AnVIL package installation | |
| RUN apt-get update && \ | |
| apt-get install -y libuv1-dev libcurl4-openssl-dev libssl-dev | |
| # If `AnVILGCP` is being installed, it relies on the `gcloud` command line utility | |
| RUN curl -fsSL https://packages.cloud.google.com/apt/doc/apt-key.gpg | gpg --batch --yes --no-tty --dearmor -o /usr/share/keyrings/cloud.google.gpg |
| This was produced in AnVIL using vjcitn/anvbiocagy:0.0.2 custom environment, after invoking "agy" and authenticating | |
| ──────────────────────────────────────────────────────────── | |
| > please write some R code that will produce a markdown table of the key data resources in this workspace | |
| ● ListDir(/home/jupyter) | |
| ● Bash(find . -maxdepth 3 -not -path '*/.*') | |
| ● ListDir(/home/jupyter/packages) | |
| ● Bash(find . -type f -not -path '*/.*') | |
| ● Bash(find . -maxdepth 2 -not -path '*/.cache*' -not -path '*/.local*' -not -path '*/.gemini*' -not -path '*/.config*' -not - |
| text = "Voyager to SpatialFeatureExperiment (SFE) aims to be analogous scater to SFE, implementing basic exploratory spatial data analysis (ESDA) and plotting. SFE inherits from SCE and SpatialExperiment (SPE), so all methods written for SCE and SPE can be used for SFE as well. | |
| In this first version, ESDA is based on the classic geospatial package spdep, but future versions will incorporate methods from GWmodel, adespatial, and etc. | |
| These are the main functionalities of the Voyager at present: | |
| Univariate global spatial statistics, such as Moran’s I, Geary’s C, permutation testing of I and C, correlograms, global G, and semivariogram. | |
| Univariate local spatial statistics, such as local Moran’s I, local Geary’s C, Getis-Ord Gi*, Moran scatter plot, and local spatial heteroscedasticity (LOSH). | |
| Multivariate spatial statistics, such as MULTISPATI PCA and a multivariate generalization of local Geary’s C. | |
| Bivariate spatial statistics, such as Lee’s L (global and local) and cross variograms. |
| library(tQTLExperiment) | |
| data(mageSEfilt, package="CSHLvc2026") | |
| plink_paths <- cache_mage_chr17_plink() | |
| ## [ cache hit ] CCDG_mage_chr17.fam | |
| ## [ cache hit ] CCDG_mage_chr17.bim | |
| ## [ cache hit ] CCDG_mage_chr17.bed | |
| ## [ validate ] Checking .bed magic bytes ... | |
| ## [ validate ] .bed magic bytes OK. | |
| plpre <- tools::file_path_sans_ext(plink_paths[["bed"]]) # works but not a list! | |
| cd <- as.data.frame(colData(mageSEfilt)) |
| #' Validate PLINK .bed magic bytes | |
| #' | |
| #' @param path Character. Local path to the .bed file. | |
| #' @return Invisibly returns \code{TRUE}; stops on failure. | |
| #' @keywords internal | |
| .validate_bed_magic <- function(path) { | |
| con <- file(path, open = "rb") | |
| on.exit(close(con)) | |
| magic <- readBin(con, what = "raw", n = 3L) | |
| expected <- as.raw(c(0x6c, 0x1b, 0x01)) |
| processing file: bkg-python-interoperability.qmd | |
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| 4/41 [libraries] | |
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| 6/41 [venv-] | |
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an instance of the Orchestrating Spatial Transcriptomics Analysis book
Jun 8 2026: use us.gcr.io/broad-dsp-gcr-public/terra-base:1.0.1 to have sudo capabilities.
To install the infrastructure, et a machine with 4 CPUs and 150 GB disk.
We use r2u to get packages and ubuntu infrastructure. Specifically, we use the script
#!/bin/bash
| #' sfe_efa_bridge.R | |
| #' | |
| #' Bridge between SpatialFeatureExperiment cell boundary polygons | |
| #' and Elliptic Fourier Analysis (Momocs). | |
| #' | |
| #' Extracts cell segmentation polygons from an SFE object, | |
| #' computes EFA coefficients per cell, stores them as a | |
| #' reducedDim or colData, and provides reconstruction/visualization. | |
| #' | |
| #' Dependencies: |
| # Set seed for reproducibility | |
| set.seed(123) | |
| # Generate 15 uniform points in the unit circle | |
| n <- 15 | |
| # Method: Generate points uniformly in unit circle using polar coordinates | |
| # We need to use square root to ensure uniform distribution | |
| r <- sqrt(runif(n)) # Square root to get uniform distribution | |
| theta <- runif(n, 0, 2*pi) |