Use new scib package (#13)

* update scib package name

* fix batch variable check between integrated and nonintegraed adata

* update environments to correct scib versions

* using pip version of scib

* fix R import issue for Harmony (as mentioned in immunogenomics/harmony#134)

* use value counts to check for batch relabeling after integration

data/generate_data.py

@@ -2,6 +2,7 @@
 import numpy as np
 import scib
 import warnings
+
 warnings.simplefilter(action='ignore', category=FutureWarning)
 
 
@@ -39,7 +40,7 @@ def get_adata_pbmc():
     """
     Code from https://scanpy-tutorials.readthedocs.io/en/latest/integrating-data-using-ingest.html
     """
-    #adata_ref = sc.datasets.pbmc3k_processed()
+    # adata_ref = sc.datasets.pbmc3k_processed()
     # quick fix for broken dataset paths, should be removed with scanpy>=1.6.0
     adata_ref = sc.read(
         "pbmc3k_processed.h5ad",

envs/scIB-python-paper.yml

@@ -3,33 +3,32 @@ channels:
   - conda-forge
   - bioconda
 dependencies:
-  - python==3.7
-  - numpy==1.18.1
+  - python=3.7
+  - numpy=1.18.1
   - pandas
   - seaborn
   - matplotlib
-  - scanpy==1.4.6
-  - anndata==0.7.1
+  - scanpy=1.4.6
+  - anndata=0.7.1
   - h5py<3
   - scipy
   - memory_profiler
-  - rpy2==3.1.0
+  - rpy2=3.1.0
   - r-stringi
-  - anndata2ri==1.0.2
-  - bbknn==1.3.9
+  - anndata2ri=1.0.2
+  - bbknn=1.3.9
   - libgcc-ng
   - gsl
   - scikit-learn
   - networkx
   - r-base
   - r-devtools
-  - r-seurat==3.1.1
+  - r-seurat=3.1.1
   - bioconductor-scater
   - bioconductor-scran
   - pip
   - numba<=0.46
   - llvmlite
-  - tensorflow==1.15
   - gxx_linux-64
   - gxx_impl_linux-64
   - gcc_linux-64
@@ -39,8 +38,8 @@ dependencies:
   - igraph
   - openblas
   - r-essentials
-  - r-globals==0.12.5
-  - r-listenv==0.8.0
+  - r-globals=0.12.5
+  - r-listenv=0.8.0
   - r-rlang
   - r-ellipsis
   - r-evaluate
@@ -52,12 +51,13 @@ dependencies:
   - r-testthat
   - r-vctrs
   - xlrd
-  - umap-learn==0.3.10
-  - louvain==0.6.1
-  - scvi==0.6.7
-  - scanorama==1.7.0
+  - umap-learn=0.3.10
+  - louvain=0.6.1
+  - scvi=0.6.7
+  - scanorama=1.7.0
   - pip:
-    - git+git://github.com/theislab/scib.git
+    - git+git://github.com/theislab/[email protected]
+    - tensorflow==1.15
     #- trvae==1.1.2
     - trvaep==0.1.0
     - mnnpy==0.1.9.5

envs/scib-pipeline.yml

@@ -14,21 +14,21 @@ dependencies:
   - openblas
   - llvmlite
   - libgcc-ng
+  - numba<=0.46  # for mnnpy
+  - anndata2ri
   - r-base
   - r-essentials
   - r-devtools
   - r-stringi
   - bioconductor-scater
   - bioconductor-scran
   # Methods
-  - scvi==0.6.7
-  - scanorama==1.7.0
-  - bbknn==1.3.9
-  - r-seurat==3.1.1
-  - numba<=0.46  # for mnnpy
-  - anndata2ri==1.0.5  # 1.0.6 has issues with HDF5 conversion
+  - scvi=0.6.7
+  - scanorama=1.7.0
+  - bbknn=1.3.9
+  - r-seurat=3.1.1
   - pip:
-    - git+git://github.com/theislab/scib.git
+    - scib==1.0.0
     - trvaep==0.1.0
     - mnnpy==0.1.9.5
     - scgen==1.1.5

scripts/integration/runIntegration.py

@@ -2,8 +2,9 @@
 # coding: utf-8
 
 import scanpy as sc
-import scIB
+import scib
 import warnings
+
 warnings.filterwarnings('ignore')
 
 
@@ -16,16 +17,15 @@ def runIntegration(inPath, outPath, method, hvg, batch, celltype=None):
     """
 
     adata = sc.read(inPath)
-    
+
     if timing:
         if celltype is not None:
-            integrated_tmp = scIB.metrics.measureTM(method, adata, batch, celltype)
+            integrated_tmp = scib.metrics.measureTM(method, adata, batch, celltype)
         else:
-            integrated_tmp = scIB.metrics.measureTM(method, adata, batch)            
+            integrated_tmp = scib.metrics.measureTM(method, adata, batch)
 
         integrated = integrated_tmp[2][0]
 
-
         integrated.uns['mem'] = integrated_tmp[0]
         integrated.uns['runtime'] = integrated_tmp[1]
 
@@ -34,10 +34,11 @@ def runIntegration(inPath, outPath, method, hvg, batch, celltype=None):
             integrated = method(adata, batch, celltype)
         else:
             integrated = method(adata, batch)
-                
+
     sc.write(outPath, integrated)
 
-if __name__=='__main__':
+
+if __name__ == '__main__':
     import argparse
 
     parser = argparse.ArgumentParser(description='Run the integration methods')
@@ -59,22 +60,22 @@ def runIntegration(inPath, outPath, method, hvg, batch, celltype=None):
     celltype = args.celltype
     method = args.method
     methods = {
-        'scanorama': scIB.integration.runScanorama,
-        'trvae': scIB.integration.runTrVae,
-        'trvaep': scIB.integration.runTrVaep,
-        'scgen': scIB.integration.runScGen,
-        'mnn': scIB.integration.runMNN,
-        'bbknn': scIB.integration.runBBKNN,
-        'scvi': scIB.integration.runScvi,
-        'scanvi': scIB.integration.runScanvi,
-        'combat': scIB.integration.runCombat,
-        'saucie': scIB.integration.runSaucie,
-        'desc': scIB.integration.runDESC
+        'scanorama': scib.integration.scanorama,
+        'trvae': scib.integration.trvae,
+        'trvaep': scib.integration.trvaep,
+        'scgen': scib.integration.scgen,
+        'mnn': scib.integration.mnn,
+        'bbknn': scib.integration.bbknn,
+        'scvi': scib.integration.scvi,
+        'scanvi': scib.integration.scanvi,
+        'combat': scib.integration.combat,
+        'saucie': scib.integration.saucie,
+        'desc': scib.integration.desc
     }
-    
+
     if method not in methods.keys():
         raise ValueError(f'Method "{method}" does not exist. Please use one of '
                          f'the following:\n{list(methods.keys())}')
-    
-    run= methods[method]
+
+    run = methods[method]
     runIntegration(file, out, run, hvg, batch, celltype)

scripts/integration/runMethods.R

@@ -11,6 +11,7 @@ getScriptPath <- function(){
 setwd(getScriptPath())
 
 library('optparse')
+library(rlang)
 require(Seurat)
 
 option_list <- list(make_option(c("-m", "--method"), type="character", default=NA, help="integration method to use"),

scripts/integration/runPost.py

@@ -1,9 +1,9 @@
 #!/usr/bin/env python
 # coding: utf-8
 
-import scanpy as sc
-import scIB
+import scib
 import warnings
+
 warnings.filterwarnings('ignore')
 
 
@@ -15,14 +15,14 @@ def runPost(inPath, outPath, conos):
         conos: set if input is conos obect
     """
     if conos:
-        adata = scIB.pp.readConos(inPath)
+        adata = scib.pp.read_conos(inPath)
     else:
-        adata = scIB.pp.readSeurat(inPath)
+        adata = scib.pp.read_seurat(inPath)
 
     adata.write(outPath)
 
 
-if __name__=='__main__':
+if __name__ == '__main__':
     import argparse
 
     parser = argparse.ArgumentParser(description='Run the integration methods')
@@ -35,5 +35,5 @@ def runPost(inPath, outPath, conos):
     file = args.input_file
     out = args.output_file
     conos = args.conos
-    
+
     runPost(file, out, conos)

scripts/integration_fail_file.py

@@ -1,8 +1,7 @@
-
 from snakemake.io import load_configfile
 from pathlib import Path
 
-if __name__=='__main__':
+if __name__ == '__main__':
     import argparse
 
     parser = argparse.ArgumentParser(description='Create an empty output file for failed integration runs')
@@ -25,31 +24,30 @@
 
     # Check inputs
     if method not in params['METHODS']:
-        raise ValueError(f'{method} is not a valid method.\n' 
+        raise ValueError(f'{method} is not a valid method.\n'
                          f'Please choose one of: {list(params["METHODS"].keys())}')
 
     if task not in params['DATA_SCENARIOS']:
-        raise ValueError(f'{task} is not a valid integration task.\n' 
+        raise ValueError(f'{task} is not a valid integration task.\n'
                          f'Please choose one of: {list(params["DATA_SCENARIOS"].keys())}')
-        
+
     # Get path values
     folder = params['ROOT']
     t_folder = task
     s_folder = 'scaled' if scale else 'unscaled'
     h_folder = 'hvg' if hvgs else 'full_feature'
     r_folder = 'R/' if 'R' in params['METHODS'][method] else ''
-    filename = method+'.h5ad'
+    filename = method + '.h5ad'
 
-    folder_path = '/'.join([folder,task,'integration',s_folder,h_folder])+'/'+r_folder
-    full_path = folder_path+filename
+    folder_path = '/'.join([folder, task, 'integration', s_folder, h_folder]) + '/' + r_folder
+    full_path = folder_path + filename
 
     if 'R' in params['METHODS'][method]:
-        filename_r = method+'.RDS'
-        full_path_r = folder_path+filename_r
+        filename_r = method + '.RDS'
+        full_path_r = folder_path + filename_r
         Path(full_path_r).touch()
-        Path(full_path_r+".benchmark").touch()
+        Path(full_path_r + ".benchmark").touch()
 
-    #print(full_path)
+    # print(full_path)
     Path(full_path).touch()
-    Path(full_path+".benchmark").touch()
-
+    Path(full_path + ".benchmark").touch()

scripts/merge_benchmarks.py

@@ -2,7 +2,7 @@
 import argparse
 import os
 
-if __name__=='__main__':
+if __name__ == '__main__':
     """
     Merge benchmark output for all scenarios, methods and settings
     """
@@ -14,7 +14,6 @@
                         help='root directory for scIB output')
     args = parser.parse_args()
 
-
     print("Searching for .benchmark files...")
     bench_files = []
     for path, dirs, files in os.walk(args.root):
@@ -43,4 +42,3 @@
     results.to_csv(args.output, index_label='scenario')
 
     print("Done!")
-

scripts/metrics/merge_metrics.py

@@ -2,35 +2,32 @@
 # coding: utf-8
 
 import pandas as pd
-import scIB
 import warnings
+
 warnings.filterwarnings('ignore')
 import argparse
 from functools import reduce
 
-if __name__=='__main__':
+if __name__ == '__main__':
     """
     Merge metrics output for all scenarios, methods and settings
     """
-    
+
     parser = argparse.ArgumentParser(description='Collect all metrics')
 
     parser.add_argument('-i', '--input', nargs='+', required=True, help='input directory')
     parser.add_argument('-o', '--output', required=True, help='output file')
-    parser.add_argument('-r', '--root', required=True, 
+    parser.add_argument('-r', '--root', required=True,
                         help='root directory for inferring column names from path')
     args = parser.parse_args()
-
-
+
     res_list = []
     for file in args.input:
         clean_name = file.replace(args.root, "").replace(".csv", "")
         res = pd.read_csv(file, index_col=0)
         res.rename(columns={res.columns[0]: clean_name}, inplace=True)
         res_list.append(res)
-    
-    results = reduce(lambda  left,right: pd.merge(left, right, left_index=True, right_index=True), res_list)
+
+    results = reduce(lambda left, right: pd.merge(left, right, left_index=True, right_index=True), res_list)
     results = results.T
     results.to_csv(args.output)
-
-