updated readme and tutorial

readme.md

@@ -1,37 +1,9 @@
-### filtering.py contains all code for Data-Driven QC
-
-####Description of functions:
- - cluster_data: performs default clustering(log normalization, HVG, PCA, neighbours, and louvain). Parameters:
-   - adata: AnnData or MultimodalData Object
-   - resolution: clustering resolution used in louvain
- - mad: finds Median Absolute Deviation for a numpy array
- - calculate_percent_ribo: calculates percent_ribo similar to how pegasus calculates percent mito. Parameters:
-   - adata: AnnData or MultimodalData Object
-   - ribo_prefix: string of regular expressions for ribosomal genes, separated by comma
- - initial_qc: does basic threshold QC based on number of genes and percent_mito. Also, identifies robust genes. Parameters:
-   - adata: AnnData or MultimodalData Object
-   - n_genes: lower threshold for n_genes
-   - percent_mito: upper threshold for percent_mito
-   - mito_prefix: mitochondrial genes prefix
-   - ribo_prefix: ribosomal genes prefix
- - metric_filter: performs filtering on a specified metric. Data must be clustered and metric must exist in obs. Parameters:
-   - adata: AnnData or MultimodalData Object
-   - method: method name for filtering (mad, outlier, cutoff)
-   - param: parameter for the selected method
-   - metric_name: name of the metric (must be in adata.obs)
-   - do_upper_co and do_lower_co: whether to do upper and lower cutoff (default: False)
-   - record_path: path for recording filtered cells CSVs (keep it None if not needed) (default: None)
- - filter_cells: performs DDQC for selected metrics. Parameters:
-   - adata: AnnData or MultimodalData Object
-   - res: clustering resolution (default 1.3)  
-   - method: method name for filtering (mad, outlier, cutoff) (default mad)
-   - threshold: parameter for the selected method (default 2)
-   - basic_n_genes: cutoff for basic filtering of n_genes (default 100)
-   - basic_percent_mito: cutoff for basic filtering of n_genes (default 80)
-   - mito_prefix: mitochondrial genes prefix (default "MT-")
-   - ribo_prefix: ribosomal genes prefix (default "^Rp[sl]\d")
-   - do_metric - set to true, if you want to filter the data based on metric (lower filtering for n_counts and n_genes, and higher filtering for percent_mito and percent_ribo)
-   - record_path: path for recording filtered cells CSVs (keep it None if not needed) (default: None) 
-
-Requirements:
-Pegasus, numpy
+# DDQC - data-driven quality control for single cell/nucleus RNA sequencing
+## installation
+1. Clone this repository using the following code:
+
+   `git clone https://github.com/ayshwaryas/ddqc.git`
+2. In the root directory run the following command:
+
+    `pip install .`
+3. For the usage instructions refer to tutorials/ddqc_tutorial.html