Update README.md

README.md

@@ -5,17 +5,53 @@ license: mit
 For more information check out our [paper](https://doi.org/10.1101/2023.10.10.561776) and [repository](https://github.com/songlab-cal/gpn).
 
 ## Querying specific variants or genes
-`scores.tsv.bgz` contains `chrom,pos,ref,alt,score` and is fast to query specific genes or positions.
-- Install `tabix`:
+
+- Install `tabix`:  
+  In your current conda environment (might be slow):
   ```bash
   conda install -c bioconda -c conda-forge htslib=1.18
   ```
-- Query a specific region (e.g. BRCA1), from remote file:  
+  or in a new conda environment:
+  ```bash
+  conda create -n tabix -c bioconda -c conda-forge htslib=1.18
+  conda activate tabix
+  ```
+- Query a specific region (e.g. BRCA1), from the remote file:  
   ```bash
   tabix https://huggingface.co/datasets/songlab/gnomad/resolve/main/scores.tsv.bgz 17:43,044,295-43,125,364
   ```
-- If you want to do many queries you might want to first download the file locally
+  The output has the following columns:  
+  | chrom | pos | ref | alt | GPN-MSA score |  
+  and would start like this:   
+  ```tsv
+  17      43044304        T       G       -5.10
+17      43044309        A       G       -3.27
+17      43044315        T       A       -6.84
+17      43044320        T       C       -6.19
+17      43044322        G       T       -5.29
+17      43044326        T       G       -3.22
+17      43044342        T       C       -4.10
+17      43044346        C       T       -2.06
+17      43044351        C       T       -0.33
+17      43044352        G       A       2.05
+  ```
+- If you want to do many queries you might want to first download the files locally
+  ```bash
+  wget https://huggingface.co/datasets/songlab/gnomad/resolve/main/scores.tsv.bgz
+  wget https://huggingface.co/datasets/songlab/gnomad/resolve/main/scores.tsv.bgz.tbi
+  ```
+  and then score:
+  ```bash
+  tabix scores.tsv.bgz 17:43,044,295-43,125,364
+  ```
 
 ## Large-scale analysis
-`test.parquet` contains coordinates, scores, and also allele frequency and consequences.
-Can be loaded, e.g., with `pd.read_parquet("test.parquet")`.
+`test.parquet` contains coordinates, scores, plus allele frequency and consequences.
+Download:
+```
+wget https://huggingface.co/datasets/songlab/gnomad/resolve/main/test.parquet
+```
+Load into a Pandas dataframe:
+```python
+df = pd.read_parquet("test.parquet")
+```