diff --git a/README.md b/README.md index 97eec06..71433f7 100644 --- a/README.md +++ b/README.md @@ -260,7 +260,7 @@ out/ └── reference2 ``` -## Output files + # :gear: Installation and Dependencies @@ -364,9 +364,9 @@ pip install numpy pandas scHPL sklearn anndata matplotlib scanpy datetime tensor - Tangram ``` -# :floppy_disk: Resources + -Add table with resource usage for different sice references and queries + # :woman_mechanic: Adding new tools @@ -433,6 +433,7 @@ snakemake -s ${snakefile} --configfile ${config} --report ${report} ## scClassify Documentation written by: Bhavyaa Chandarana + Date written: 2023-07 scClassify workflow was generated using the tutorial below: @@ -451,6 +452,7 @@ https://www.bioconductor.org/packages/release/bioc/vignettes/scClassify/inst/doc ## scPred Documentation written by: Alva Annett + Date written: 2023-07 Normalization and parameters based on this tutorial: @@ -476,6 +478,7 @@ http://www.bioconductor.org/packages/devel/bioc/vignettes/SingleR/inst/doc/Singl ## singleCellNet Documentation written by: Rodrigo Lopez Gutierrez + Date written: 2023-08-01 singleCellNet workflow was generated following the tutorial below: @@ -490,6 +493,7 @@ Normal parameters were used in both the training and prediction functions, with ## Correlation Documentation written by: Rodrigo Lopez Gutierrez + Date written: 2023-08-02 The Correlation tool runs a correlation-based cell type prediction on a sample of interest, given the mean gene expression per label for a reference. @@ -507,6 +511,7 @@ Currently only outputting a table with each cell, the most highly correlated lab ## scLearn Documentation written by: Bhavyaa Chandarana, updated by Tomas Vega Waichman + Date written: 2023-08-04 scLearn workflow was generated using the following tutorial: https://github.com/bm2-lab/scLearn#single-label-single-cell-assignment @@ -524,6 +529,7 @@ scLearn workflow was generated using the following tutorial: https://github.com/ ## singleCellNet Documentation written by: Rodrigo Lopez Gutierrez + Date written: 2023-08-01 singleCellNet workflow was generated following the tutorial below: @@ -538,6 +544,7 @@ Normal parameters were used in both the training and prediction functions, with ## ACTINN Documentation written by: Alva Annett + Date written: 2023-08-08 ACTINN code is based on `actinn_format.py` and `actinn_predict.py` originally found here: https://github.com/mafeiyang/ACTINN @@ -549,6 +556,7 @@ ACTINN code is based on `actinn_format.py` and `actinn_predict.py` originally fo ## Tangram Documentation written by: Tomas Vega Waichman + Date written: 2023-08-08 The Tangram workflow was generated following the tutorial provided below: @@ -567,6 +575,7 @@ It is necessary to explore whether parallelization is possible. ## scAnnotate Documentation written by: Tomas Vega Waichman + Date written: 2023-08-11 The scAnnotate workflow was generated following the tutorial provided below: @@ -581,6 +590,7 @@ https://cran.r-project.org/web/packages/scAnnotate/vignettes/Introduction.html ## scID Documentation written by: Tomas Vega Waichman + Date written: 2023-08-12 The scID workflow was generated following the tutorials provided below: @@ -603,6 +613,7 @@ R CMD INSTALL MAST_1.26.0.tar.gz ## scNym Documentation written by: Tomas Vega Waichman + Date written: 2023-08-14 The scNym workflow was generated following the tutorial provided below: @@ -622,12 +633,15 @@ confidence scores." ## CellTypist Documentation written by: Tomas Vega Waichman + Date written: 2023-08-16 The CellTypist workflow was generated following the tutorials provided below: + Training: * https://celltypist.readthedocs.io/en/latest/celltypist.train.html * https://github.com/Teichlab/celltypist#supplemental-guidance-generate-a-custom-model + Predicting: * https://celltypist.readthedocs.io/en/latest/notebook/celltypist_tutorial_ml.html