Update README.md

Author: yztxwd

README.md

@@ -8,21 +8,17 @@ https://doi.org/10.1186/s13059-020-02218-6
 
 ## Installation and Requirements 
 
-**Please Note**: This repository has been updated as of **02/11/2021**. Input file formats have been modified to increase readability.   
-python >= 3.5  
-We suggest using anaconda to create a virtual environment using the provided YAML configuration file:
-`conda env create -f bichrom.yml`  
+~~**Please Note**: This repository has been updated as of **02/11/2021**. Input file formats have been modified to increase readability.~~
 
-Alternatively, to install requirements using pip: 
-`pip install -r requirements.txt`
+**Please Note**: As of **03/07/2022**, the tensorflow version used by Bichrom has been changed to **2.6.2**, cudatoolkit and cudnn versions are included in `bichrom.yml`.
 
-**Note**: Bichrom uses Pybedtools to construct genome-wide training, test and validation datasets. In order to use this functionality, you must have bedtools installed. To install bedtools, follow instructions here: https://bedtools.readthedocs.io/en/latest/content/installation.html 
+We suggest using anaconda to create a virtual environment using the provided YAML configuration file:
+`conda env create -f bichrom.yml`  
 
-**Note**: For GPU compatibility, tensorflow 2.2.1 requires CUDA 10.1 and cuDNN >= 7.
+**Note**: Now Bichrom supports **MirroredStrategy** to employ multiple gpus for training.
 
 ## Usage
 
-
 ### Step 1 - Construct Bichrom Input Data
 
 Clone and navigate to the Bichrom repository. 
@@ -52,7 +48,11 @@ optional arguments:
                         format
   -o OUTDIR, --outdir OUTDIR
                         Output directory for storing train, test data
-
+  -p PROCESSORS         Number of processors
+  -val_chroms CHROMOSOME
+                        Space-delimited chromosome names would be used as validation dataset
+  -test_chroms CHROMOSOME
+                        Space-delimited chromosome names would be used as test dataset
 ```
 
 **Required Arguments**
@@ -89,6 +89,10 @@ Output directory for storing output train, test and validation datasets.
 A blacklist BED file, with artifactual regions to be excluded from the training.  
 For an example file, please see: `sample_data/mm10_blacklist.bed`.
 
+**p** (optional):    
+Number of processors, default is 1.    
+It is suggested to provide more cores to speed up training sample preparation
+
 ### Step 1 - Output 
 construct_data.py will produce train, test and validation datasets in the specified output directory.
 This function will also produce a configuration file called **bichrom.yaml**, which can be used as input to run Bichrom. This configuration file stores the paths to the created train, test and validation datasets. 
@@ -144,24 +148,9 @@ Bichrom output directory.
   * best_model.hdf5: A Bichrom tensorflow.Keras Model (with the highest validation set auPRC)
   * precision-recall curves for the sequence-only network and Bichrom.
 
-### Optional: Custom Training Sets and YAML files
-If generating custom training data, please specify a custom YAML file for training Bichrom. Bichrom requires the following files: **1)** Training files, **2)** Validation files, **3)** Test Files. 
-
-Within each category, Bichrom expects **3 file types**: 
-* **Sequence File**: This file contains sequence data (one training sequence of lenght L/line). Acceptable nucleotides: A, T, G, C, N. 
-For an example: see `custom_data_files/data_train.seq`.
-
-
-* **Chromatin Files**: 1 file per chromatin experiment. Each input chromatin file contains chromatin signal (binned at any resolution) over the input genomic windows.    
-For an example: see `custom_data_files/data_train.mES_dnaseseq.chromatin` which is uses a window length= 500, nbins=20.
-
-
-* **Labels File**: This file contains binary labels associated with TF binding over the input genomic windows.  
-For an example: see `custom_data_files/data_train.labels`
-
-
-File paths to these files should be summarized in a configuration YAML file. For the structure of the YAML file, please see:   `sample_data/sample_custom_config.yaml` or `custom_data_files/bichrom.yaml`
+~~### Optional: Custom Training Sets and YAML files~~
 
+**TODO**: Due to currently Bichrom saving dataset in Tensorflow TFRecord format, a new way of providing custom training set and yaml files will be released.
 
 ### 2-D Bichrom embeddings
 For 2-D latenet embeddings, please refer to the README in the ```Bichrom/latent_embeddings directory```