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Merge branch 'master' into issue-297
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csangara committed Aug 29, 2024
2 parents 11ba965 + 842946d commit 9508523
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58 changes: 58 additions & 0 deletions .github/workflows/check-standard.yaml
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# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
on:
workflow_dispatch:
pull_request:

name: check-standard

permissions: read-all

jobs:
check-standard:
runs-on: ${{ matrix.config.os }}

name: ${{ matrix.config.os }} (${{ matrix.config.r }})

strategy:
fail-fast: false
matrix:
config:
- {os: macos-latest, r: 'release'}
- {os: windows-latest, r: 'release'}
- {os: ubuntu-latest, r: 'devel', http-user-agent: 'release'}
- {os: ubuntu-latest, r: 'release'}
- {os: ubuntu-latest, r: 'oldrel-1'}

env:
GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
R_KEEP_PKG_SOURCE: yes

steps:
- uses: actions/checkout@v4

- uses: r-lib/actions/setup-pandoc@v2

- uses: r-lib/actions/setup-r@v2
with:
r-version: ${{ matrix.config.r }}
http-user-agent: ${{ matrix.config.http-user-agent }}
use-public-rspm: true

- uses: r-lib/actions/setup-r-dependencies@v2
with:
dependencies: '"hard"'
extra-packages: |
any::rcmdcheck
any::testthat
any::knitr
any::rmarkdown
local::.
needs: check

- uses: r-lib/actions/check-r-package@v2
with:
upload-snapshots: true
args: 'c("--no-manual","--no-build-vignettes","--no-examples")'
build_args: 'c("--no-manual","--no-build-vignettes", "--no-resave-data")'
error-on: '"error"'
5 changes: 3 additions & 2 deletions DESCRIPTION
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@@ -1,7 +1,7 @@
Package: nichenetr
Type: Package
Title: NicheNet: Modeling Intercellular Communication by Linking Ligands to Target Genes
Version: 2.1.5
Version: 2.1.7
Authors@R: c(person("Robin", "Browaeys", role = c("aut")),
person("Chananchida", "Sang-aram", role = c("aut", "cre"), email = "[email protected]"))
Description: This package allows you the investigate intercellular communication from a computational perspective. More specifically, it allows to investigate how interacting cells influence each other's gene expression. Functionalities of this package (e.g. including predicting extracellular upstream regulators and their affected target genes) build upon a probabilistic model of ligand-target links that was inferred by data-integration.
Expand All @@ -12,6 +12,7 @@ URL: https://github.com/saeyslab/nichenetr
BugReports: https://github.com/saeyslab/nichenetr/issues
RoxygenNote: 7.3.1
Depends: R (>= 3.0.0)
biocViews:
Imports:
tidyverse,
data.table,
Expand All @@ -27,7 +28,6 @@ Imports:
fdrtool,
ROCR,
caTools,
limma,
Hmisc,
caret,
randomForest,
Expand All @@ -52,6 +52,7 @@ Suggests:
rmarkdown,
testthat,
doMC,
limma,
mco,
parallel,
covr,
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1 change: 0 additions & 1 deletion NAMESPACE
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Expand Up @@ -185,7 +185,6 @@ importFrom(igraph,get.data.frame)
importFrom(igraph,graph_from_adjacency_matrix)
importFrom(igraph,page_rank)
importFrom(igraph,sample_degseq)
importFrom(limma,wilcoxGST)
importFrom(magrittr,set_colnames)
importFrom(magrittr,set_rownames)
importFrom(purrr,reduce)
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9 changes: 7 additions & 2 deletions R/characterization_data_sources.R
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Expand Up @@ -353,10 +353,15 @@ evaluate_model = function(parameters_setting, lr_network, sig_network, gr_networ
ligand_importances$spearman[is.na(ligand_importances$spearman)] = 0
ligand_importances$pearson_log_pval[is.na(ligand_importances$pearson_log_pval)] = 0
ligand_importances$spearman_log_pval[is.na(ligand_importances$spearman_log_pval)] = 0
ligand_importances$mean_rank_GST_log_pval[is.na(ligand_importances$mean_rank_GST_log_pval)] = 0
ligand_importances$pearson_log_pval[is.infinite(ligand_importances$pearson_log_pval)] = 10000
ligand_importances$spearman_log_pval[is.infinite(ligand_importances$spearman_log_pval)] = 10000
ligand_importances$mean_rank_GST_log_pval[is.infinite(ligand_importances$mean_rank_GST_log_pval)] = 10000

if ("mean_rank_GST_log_pval" %in% colnames(ligand_importances)){
ligand_importances$mean_rank_GST_log_pval[is.na(ligand_importances$mean_rank_GST_log_pval)] = 0
ligand_importances$mean_rank_GST_log_pval[is.infinite(ligand_importances$mean_rank_GST_log_pval)] = 10000
} else{
warning("mean_rank_GST_log_pval not in ligand_importances; do you have limma installed?")
}

all_importances = ligand_importances %>% select_if(.predicate = function(x){sum(is.na(x)) == 0})
# all_importances = full_join(ligand_importances, ligand_importances_glm, by = c("setting","test_ligand","ligand")) %>% full_join(ligand_importances_discrete, by = c("setting","test_ligand", "ligand"))
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