diff --git a/README.md b/README.md index 53c25e5..cd219fa 100644 --- a/README.md +++ b/README.md @@ -7,7 +7,7 @@ The code is listed in order of execution, e.g. "1_", "2_" etc. The output of eac The logic for these analyses is contained in the `SingleCellProteogenomics` folder. -The input files are contained in the "input" folder. This folder is linked [here](https://drive.google.com/file/d/1G4i115FCH8XNyiEHCkBXMSO_9pwGflTq/view?usp=sharing) as a zip file, `input.zip`. Expand this folder within the base directory of this repository. If you are looking for the raw imaging proteomic dataset produced after filtering artifacts and such, that is located [here](https://drive.google.com/file/d/11vjsZV-nmzPpFmA7ShbfHzmbrk057b1V/view?usp=sharing). +The input files are contained in the "input" folder. This folder is linked [here for release v1.2](https://drive.google.com/file/d/149ICTtieYjuKWZoLwRLzimwff0n6eWqw/view?usp=sharing) as a zip file, `input.zip`. Expand this folder within the base directory of this repository. If you are looking for the raw imaging proteomic dataset produced after filtering artifacts and such, that is located [here](https://drive.google.com/file/d/11vjsZV-nmzPpFmA7ShbfHzmbrk057b1V/view?usp=sharing). The output files are added to a folder "output" during the analysis, and figures are added to a folder "figures." @@ -27,11 +27,11 @@ This workflow can be run using `snakemake`: The single-cell RNA-Seq data is available at GEO SRA under project number [GSE146773](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146773). -The cell cycle phase and FACS intensity information for these ~1,000 cells are contained in the [input folder](https://drive.google.com/file/d/1G4i115FCH8XNyiEHCkBXMSO_9pwGflTq/view?usp=sharing) within three files, one per plate, starting with `RNAData/180911_Fucci_single cell seq_ss2-18-*.csv`. +The cell cycle phase and FACS intensity information for these ~1,000 cells are contained in the [input folder](https://drive.google.com/file/d/149ICTtieYjuKWZoLwRLzimwff0n6eWqw/view?usp=sharing) within three files, one per plate, starting with `RNAData/180911_Fucci_single cell seq_ss2-18-*.csv`. The `snakemake` workflow used to analyze the scRNA-Seq dataset, including RNA velocity calculations and louvain unsupervised clustering, can be found in this repository: https://github.com/CellProfiling/FucciSingleCellSeqPipeline. -The `loom` file containing the results of RNA velocity analysis, including spliced and unspliced counts, can be found in the [input folder](https://drive.google.com/file/d/1mdQbYcDPqiTOHeiYbv_4RtrxrmlhYMNl/view?usp=sharing) under `RNAData/a.loom`, and the observation names used for each cell that match the "Well_Plate" identifiers can be found in `RNAData/a.obs_names.csv`. +The `loom` file containing the results of RNA velocity analysis, including spliced and unspliced counts, can be found in the [input folder](https://drive.google.com/file/d/149ICTtieYjuKWZoLwRLzimwff0n6eWqw/view?usp=sharing) under `RNAData/a.loom`, and the observation names used for each cell that match the "Well_Plate" identifiers can be found in `RNAData/a.obs_names.csv`. ## Citation diff --git a/workflow/Snakefile b/workflow/Snakefile index c9e480c..ab2257e 100644 --- a/workflow/Snakefile +++ b/workflow/Snakefile @@ -1,6 +1,6 @@ import os -INPUTID="1G4i115FCH8XNyiEHCkBXMSO_9pwGflTq" +INPUTID="149ICTtieYjuKWZoLwRLzimwff0n6eWqw" # scripts currently expect base directory as working directory if os.path.basename(os.path.abspath(os.curdir)) == "workflow":