Add row counts, fix loading code bug

- Add statistics table with row counts (peaks: 83K, fragments: 58M)
- Fix variable name bug in peaks loading (peak_file -> peak_path)
- Remove grelu.io.bed import (use pandas directly)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

README.md

@@ -17,35 +17,40 @@ This dataset contains pseudobulk scATAC-seq data for human microglia, derived fr
 
 ## Dataset Structure
 
-The dataset is divided into two configurations: `peaks` and `fragments`.
+The dataset is divided into two files: peaks and fragments.
 
-### 1. Peaks Configuration (`peak_file.narrowPeak`)
-Standard ENCODE narrowPeak format (tab-separated).
-- `chrom`: Chromosome / Contig name.
-- `start`: 0-based start position.
-- `end`: End position.
-- `name`: Peak identifier.
-- `score`: Integer score for display.
-- `strand`: Orientation.
-- `signalValue`: Measurement of overall enrichment.
-- `pValue`: Statistical significance (-log10).
-- `qValue`: False discovery rate (-log10).
-- `peak`: Point-source (summit) relative to start.
+### Statistics
+| File | Rows | Description |
+|------|------|-------------|
+| `peak_file.narrowPeak` | 83,320 | Called ATAC-seq peaks |
+| `fragment_file.bed` | 57,919,016 | Individual ATAC-seq fragments |
 
-### 2. Fragments Configuration (`fragment_file.bed`)
+### 1. Peaks file (`peak_file.narrowPeak`)
+Standard ENCODE narrowPeak format (tab-separated, no header).
+- `chrom`: Chromosome / Contig name
+- `start`: 0-based start position
+- `end`: End position
+- `name`: Peak identifier
+- `score`: Integer score for display
+- `strand`: Orientation
+- `signalValue`: Measurement of overall enrichment
+- `pValue`: Statistical significance (-log10)
+- `qValue`: False discovery rate (-log10)
+- `peak`: Point-source (summit) relative to start
+
+### 2. Fragments file (`fragment_file.bed`)
 Standard BED6 format representing individual ATAC-seq fragments.
-- `chrom`: Chromosome.
-- `start`: Start position.
-- `end`: End position.
-- `source`: Sequencing run identifier (e.g., `SRR11442505`).
-- `score`: Placeholder (0).
-- `strand`: Orientation.
+- `chrom`: Chromosome
+- `start`: Start position
+- `end`: End position
+- `source`: Sequencing run identifier (e.g., `SRR11442505`)
+- `score`: Placeholder (0)
+- `strand`: Orientation
 
 ## Usage
 
 ```python
 from huggingface_hub import hf_hub_download
-import grelu.io.bed
 import pandas as pd
 
 peak_path = hf_hub_download(
@@ -53,14 +58,13 @@ peak_path = hf_hub_download(
     repo_type="dataset",
     filename="peak_file.narrowPeak"
 )
-peaks = grelu.io.bed.read_narrowpeak(peak_file)
+peaks = pd.read_csv(peak_path, sep='\t', header=None)
 
 frag_path = hf_hub_download(
     repo_id="Genentech/microglia-scatac-tutorial-data",
     repo_type="dataset",
     filename="fragment_file.bed"
 )
-fragments = pd.read_csv(frag_path, sep='\t', header=None, 
+fragments = pd.read_csv(frag_path, sep='\t', header=None,
                         names=['chrom', 'start', 'end', 'source', 'score', 'strand'])
-
-```
+```