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case1: only qc
Find cellbin2/Stereo-CITE_T_FF.json
change run like follows

"run": {
    "qc": true,
    "alignment": false,
    "matrix_extract": false,
    "report": false,
    "annotation": false
  }

run command like below

python cellbin2/cellbin_pipeline.py \
-c SN \
-i SN.tif \
-imf SN_IF.tif \
-o result/SN \
-s DAPI

case2: only alignment with registration
This mode assumes you have already done qc
Find corresponding json, change run like follows 

"run": {
    "qc": false,
    "alignment": true,
    "matrix_extract": false,
    "report": false,
    "annotation": false
  }

run command like below
-o path should be the same as qc

python cellbin2/cellbin_pipeline.py \
-c SN \
-i SN.tif \
-s DAPI \
-imf SN_IF.tif \
-m SN.raw.gef \
-k "Stereo-CITE_T_FF_V1.0" \
-o result/SN

case3: only alignment without registration & matrix extract
This mode assumes the input image is aligned, so only run tissue and cell seg
If kit type is Stereo-CITE_T_FF_V1.0, you find Stereo-CITE_T_FF.json under cellbin2/config
change run like follows

"run": {
    "qc": false,
    "alignment": true,
    "matrix_extract": true,
    "report": false,
    "annotation": false
  }

case 4: No matrix
Stereo-seq_T_FF ssDNA

-c SN 
-i /Path/TO/SN_fov_stitched_ssDNA.tif 
-s ssDNA 
-o /Path/TO//test/SN 
-k "Stereo-seq_T_FF_V1.2"

case 5: Create bin1 matrix image

cd cellbin2/matrix
python matrix.py \
-i {SN.gem.gz/SN.gef file path}
-o {output_folder}