BS-Deconvolution

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<title>BS-Deconvolution/README.md at master · ltlam/BS-Deconvolution</title>
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BS-Deconvolution

Step 1 - union of reference methylation calls

[in] -b_ref --beds_ref = list of bed graph files
[in] -s_ref --sorted_ref = sorted bed graph files, 0=unsorted,1=sorted
[in] -out_ref --out_ref = output file name
[in] -p_ref --process_ref = number of threads (default 1)

requirements:

python 2.7.11 - https://www.python.org/downloads/release/python-2711/
pandas - https://github.com/pydata/pandas.git

cd <BS-Deconvolution dir>
python ./scripts/meth_matrix.py -b_ref ./test_ref/CD14_1.txt,./test_ref/CD14_2.txt,./test_ref/CD14_3.txt,./test_ref/Macrophage_1.txt,./test_ref/Macrophage_2.txt,./test_ref/Macrophage_3.txt,./test_ref/Neutrophil_1.txt,./test_ref/Neutrophil_2.txt,./test_ref/Neutrophil_3.txt -out_ref ./cpg_pipe_out/meth_table.txt

Step 2 - calculate distance metrics

[in] -in_metric --unioned_reference = path to tab delimeted union of reference methylation
[in] -t_metric --types_metric = comma separated list of corresponding cell types and file number
[in] -g_metric --group_metric = comma separated list of cell type groups
[in] -out_metric --out_metric = output file name

requirements:

python 2.7.11 - https://www.python.org/downloads/release/python-2711/
scipy - https://sourceforge.net/projects/scipy/files/scipy/
numpy - https://sourceforge.net/projects/numpy/files/NumPy/

cd <BS-Deconvolution dir>
python ./scripts/matrix_metrics.py -in_metric ./cpg_pipe_out/meth_table.txt -t_metric CD14:1,2,3|Macrophage:4,5,6|Neutrophil:7,8,9 -g_metric CD14,Macrophage,Neutrophil"|"CD14,Macrophage"|"CD14,Neutrophil -out_metric ./cpg_pipe_out/meth_metrics.txt

Step 3 - merge sample methylation files

[in] -in_sam --in_sam = comma separated list of cgmap files
[in] -out_sam --out_sam = output file name
[in] -f_sam --filter context CG,CHG,CHH
[in] -cov_sam --min_cov = minimum cover threshold
[in] -s_sam --sorted = sort file 0=unsorted, 1=sorted
[in] -p_sam --proc_sam = number of threads (default 1)

requirements:

python 2.7.11 - https://www.python.org/downloads/release/python-2711/
pandas - https://github.com/pydata/pandas.git
numpy - https://sourceforge.net/projects/numpy/files/NumPy/

cd <BS-Deconvolution dir>
python ./scripts/cgmap_data_frame.py -in_sam ./test_sam/test1_shuffle.CGmap,./test_sam/test2_shuffle.CGmap,./test_sam/test3_shuffle.CGmap -out_sam ./cpg_pipe_out/meth_sample.txt -f_sam CG -cov_sam 10

Step 4 - join reference methylation with metrics to sample methylation and calculate extreme cell types

[in] -in_join_ref --ref_metric = path to reference methylation and metrics file
[in] -in_join_ref --out = join output file name
[in] -in_join_sam --sam_meth = path to sample methylation file
[in] -ext --ext_cols = comma separated list of extreme columns

requirements:

python 2.7.11 - https://www.python.org/downloads/release/python-2711/
pandas - https://github.com/pydata/pandas.git
numpy - https://sourceforge.net/projects/numpy/files/NumPy/

cd <BS-Deconvolution dir>
python ./scripts/join_ref_sample.py -in_join_ref ./cpg_pipe_out/meth_metrics.txt -in_join_sam ./cpg_pipe_out/meth_sample.txt -out_join ./cpg_pipe_out/meth_join.txt -ext max_CD14:CD14_min_CD14.Macrophage.Neutrophil,CD14_min_CD14.Macrophage

Step 5 - filter CpG sites by anova_p, distance metrics, and select the top n sites

[in] -in_filter --refsam_matrix = path to comma separated file with reference and sample methylation values
[in] -out_filter --out_refsam = output csv of filter methylation values
[in] -sl_filter --sample_labels_f = comma separated list of sample labels
[in] -ml_filter --metric_list = comma separated list of metric labels to filter
[in] -hn_filter --hi_n_meth = top n rows per hypermethylation metric
[in] -ln_filter --lo_n_meth = top n rows per hypomethylation metric
[in] -p_filter --pval = anova p value filter

requirements:

python 2.7.11 - https://www.python.org/downloads/release/python-2711/
pandas - https://github.com/pydata/pandas.git

cd <BS-Deconvolution dir>
python ./scripts/filter_ref_sample.py -in_filter ./cpg_pipe_out/meth_join.txt -out_filter ./cpg_pipe_out/meth_filtered.txt -sl_filter test1_shuffle,test2_shuffle,test3_shuffle -ml CD14_min_CD14.Macrophage.Neutrophil,Macrophage_min_CD14.Macrophage.Neutrophil,Neutrophil_min_CD14.Macrophage.Neutrophil,CD14_min_CD14.Macrophage,Macrophage_min_CD14.Macrophage,CD14_min_CD14.Neutrophil,Neutrophil_min_CD14.Neutrophil

Step 6 - estimate proportions using bounded least squares regression

[in] -in_reg --filter_matrix = comma separated file of filtered CpG sites with reference and sample methylation calls
[in] -out_reg --output_coeff_csv = csv output of coefficients
[in] -rt_reg --reference_types = comma separated list of reference types from the filter matrix column header
[in] -sl_reg --sample_labels = comma separated list of samples from the filter matrix column header

requirements:

python 2.7.11 - https://www.python.org/downloads/release/python-2711/
R - https://cran.r-project.org/mirrors.html

cd <BS-Deconvolution dir>
python ./scripts/decon_int_est.py -in_reg ./cpg_pipe_out/meth_filtered.txt -out_reg ./cpg_pipe_out/coeff.csv -rt_reg CD14,Macrophage,Neutrophil -sl_reg test1_shuffle,test2_shuffle,test3_shuffle

CpG Pipeline

[in] -o --out_folder = path to output folder

requirements:

python 2.7.11 - https://www.python.org/downloads/release/python-2711/
pandas - https://github.com/pydata/pandas.git
scipy - https://sourceforge.net/projects/scipy/files/scipy/
numpy - https://sourceforge.net/projects/numpy/files/NumPy/

cd <BS-Deconvolution dir>
python ./scripts/cpg_decon_pipeline.py -b_ref ./test_ref/CD14_1.txt,./test_ref/CD14_2.txt,./test_ref/CD14_3.txt,./test_ref/Macrophage_1.txt,./test_ref/Macrophage_2.txt,./test_ref/Macrophage_3.txt,./test_ref/Neutrophil_1.txt,./test_ref/Neutrophil_2.txt,./test_ref/Neutrophil_3.txt -t_metric CD14:1,2,3"|"Macrophage:4,5,6"|"Neutrophil:7,8,9 -g_metric CD14,Macrophage,Neutrophil"|"CD14,Macrophage"|"CD14,Neutrophil -o ./cpg_pipe_out -in_sam ./test_sam/test1_shuffle.CGmap,./test_sam/test2_shuffle.CGmap,./test_sam/test3_shuffle.CGmap -ext max_CD14:CD14_min_CD14.Macrophage.Neutrophil,CD14_min_CD14.Macrophage -d_filter 0.05 -p_filter 1.0 -rt_reg CD14,Macrophage,Neutrophil

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BS-Deconvolution

Step 1 - union of reference methylation calls

requirements:

Step 2 - calculate distance metrics

requirements:

Step 3 - merge sample methylation files

requirements:

Step 4 - join reference methylation with metrics to sample methylation and calculate extreme cell types

requirements:

Step 5 - filter CpG sites by anova_p, distance metrics, and select the top n sites

requirements:

Step 6 - estimate proportions using bounded least squares regression

requirements:

CpG Pipeline

requirements:

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BS-Deconvolution

Step 1 - union of reference methylation calls

requirements:

Step 2 - calculate distance metrics

requirements:

Step 3 - merge sample methylation files

requirements:

Step 4 - join reference methylation with metrics to sample methylation and calculate extreme cell types

requirements:

Step 5 - filter CpG sites by anova_p, distance metrics, and select the top n sites

requirements:

Step 6 - estimate proportions using bounded least squares regression

requirements:

CpG Pipeline

requirements:

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