snapatac2.tl.macs3 command encountered an error using the call_broad_peaks function

[haloudashu]

Hi Dr. Zhang
Thank you great contribution to scalable scATAC analysis tools. I use snapatac2 version 2.8.0 to read a 93Mb fragment file as Anndata, and then use snapatac2.tl.macs3 to make a boradPeak calling:

import snapatac2 as snap

snap.tl.macs3(atac, 
              qvalue=0.05, 
              nolambda=False, 
              shift=0, 
              extsize=400, 
              min_len=400, 
              blacklist=None, 
              call_broad_peaks=True, 
              broad_cutoff=0.1, 
              n_jobs=4)

Run time report error:

2025-02-18 10:38:44 - INFO - [836 MB] #3 Pre-compute pvalue-qvalue table...
2025-02-18 10:39:32 - INFO - [1257 MB] #3 Call peaks for each chromosome...
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[12], line 1
----> 1 snap.tl.macs3(atac, qvalue=qvalue, nolambda=nolambda, shift=snapshift, extsize=extsize, min_len=min_len, blacklist=None, call_broad_peaks=broad, broad_cutoff=broad_cutoff, n_jobs=core)

File snapatac2/tools/_call_peaks.py:145, in macs3(adata, groupby, qvalue, call_broad_peaks, broad_cutoff, replicate, replicate_qvalue, max_frag_size, selections, nolambda, shift, extsize, min_len, blacklist, key_added, tempdir, inplace, n_jobs)
    142 options.scanwindow = 2 * options.d
    144 if groupby is None:
--> 145     peaks = _snapatac2.call_peaks_bulk(adata, options, max_frag_size)
    146     if inplace:
    147         adata.uns[key_added + "_pseudobulk"] = peaks.to_pandas() if not adata.isbacked else peaks

AttributeError: 'MACS3.IO.PeakIO.BroadPeakIO' object has no attribute 'peaks'

Excuse me, is this a bug?
I referred to issue # 365 and found that this method requires a significant amount of memory resources. Is there any better solution?
Thank you!