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116
upload_jsons/upload_jsons_scripts/counts_bigwig_uploads/chrombpnet/atac_prepare.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,116 @@ | ||
| import os | ||
| import json | ||
| import pandas as pd | ||
| import pybedtools | ||
|
|
||
| encids = ["K562", "HEPG2", "IMR90", "H1ESC", "GM12878"] | ||
| #encids = ["K562", "HEPG2"] | ||
| #encids = [ "IMR90", "H1ESC", "GM12878"] | ||
|
|
||
| def make_bb_file(in_bed, out_bb): | ||
| assert(os.path.isfile("atac_temp.bed")==False) | ||
| command = "zcat "+in_bed+" | LC_COLLATE=C sort -k1,1 -k2,2n > atac_temp.bed" | ||
| print(command) | ||
| os.system(command) | ||
|
|
||
| command = "bedToBigBed atac_temp.bed /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/reference/chrom.sizes "+out_bb | ||
| print(command) | ||
| os.system(command) | ||
|
|
||
|
|
||
| command = "rm atac_temp.bed" | ||
| print(command) | ||
| os.system(command) | ||
|
|
||
| chrs = list(map(str,list(range(1,23)))) | ||
| chrs = ['chr'+i for i in chrs] | ||
| chrs = chrs + ['chrX', 'chrY'] | ||
|
|
||
| def make_sel_bedfile(in_bed, out_bed): | ||
| input_bed = pd.read_csv(in_bed, sep="\t", header=None) | ||
| print(input_bed.shape) | ||
| input_bed = input_bed[input_bed[0].isin(chrs)] | ||
| print(input_bed.shape) | ||
|
|
||
| input_bed[1] = input_bed[1]+input_bed[9]-500 | ||
| input_bed[2] = input_bed[1] + 1000 | ||
| print(input_bed.head()) | ||
| x = pybedtools.BedTool.from_dataframe(input_bed[[0,1,2]]) | ||
| x = x.sort().merge() | ||
| output_bed = x.to_dataframe() | ||
| print(output_bed.shape) | ||
| print(output_bed.head()) | ||
| output_bed.to_csv(out_bed, sep='\t', header=False, index=False) | ||
|
|
||
| encode_id = {"K562": "ENCSR868FGK", | ||
| "GM12878": "ENCSR637XSC", | ||
| "HEPG2": "ENCSR291GJU", | ||
| "IMR90": "ENCSR200OML", | ||
| "H1ESC": "GSE267154"} | ||
|
|
||
| odir='atac/' | ||
| for encid in encids: | ||
| print(encid) | ||
| ofile = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/ATAC/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.counts_scores_new_compressed.stats" | ||
| if os.path.isfile(ofile): | ||
| counts_bw = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/ATAC/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.counts_scores_new_compressed.bw" | ||
| else: | ||
| print(ofile) | ||
| ofile = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/ATAC/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.counts_scores.stats" | ||
| if os.path.isfile(ofile): | ||
| counts_bw = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/ATAC/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.counts_scores.bw" | ||
| else: | ||
| counts_bw = None | ||
| print(ofile) | ||
| continue | ||
|
|
||
|
|
||
| ofile = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/ATAC/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.profile_scores_new_compressed.stats" | ||
| if os.path.isfile(ofile): | ||
| profile_bw = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/ATAC/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.profile_scores_new_compressed.bw" | ||
| else: | ||
| print(ofile) | ||
| ofile = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/ATAC/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.profile_scores.stats" | ||
| if os.path.isfile(ofile): | ||
| profile_bw = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/ATAC/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.profile_scores.bw" | ||
| else: | ||
| profile_bw = None | ||
| print(ofile) | ||
|
|
||
| continue | ||
|
|
||
| ofile = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/ATAC/"+encid+"/interpret_upload/average_preds/per_folds.inputs.bed.gz" | ||
| if os.path.isfile(ofile): | ||
| sel_path = os.path.join("/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/ATAC/", encid+"/interpret_upload/average_preds/selected.regions.valid.merged.bed.gz" ) | ||
| sel_path_bb = os.path.join("/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/ATAC/", encid+"/interpret_upload/average_preds/selected.regions.valid.merged.bigBed" ) | ||
| if not os.path.isfile(sel_path): | ||
| make_sel_bedfile(ofile, sel_path) | ||
|
|
||
| if os.path.isfile(sel_path) and (not os.path.isfile(sel_path_bb)): | ||
| make_bb_file(sel_path, sel_path_bb) | ||
|
|
||
| else: | ||
| sel_path=None | ||
| sel_path_bb=None | ||
| print(ofile) | ||
| continue | ||
|
|
||
| assert(os.path.isfile(counts_bw)==True) | ||
| assert(os.path.isfile(profile_bw)==True) | ||
|
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||
|
|
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| output_json = {} | ||
| output_json["experiment"] = encode_id[encid] | ||
| output_json["counts sequence contribution scores bigWig"] = counts_bw | ||
| output_json["profile sequence contribution scores bigWig"] = profile_bw | ||
|
|
||
| if os.path.isfile(sel_path_bb): | ||
| output_json["selected regions for predicted signal and sequence contribution scores bigBed"] = sel_path_bb | ||
|
|
||
| if os.path.isfile(sel_path): | ||
| output_json["selected regions for predicted signal and sequence contribution scores bed"] = sel_path | ||
|
|
||
| if not os.path.isfile(odir+encode_id[encid]+".json"): | ||
| f = open(odir+encode_id[encid]+".json", "w") | ||
| json.dump(output_json, f, indent=4) | ||
| f.close() |
115 changes: 115 additions & 0 deletions
115
upload_jsons/upload_jsons_scripts/counts_bigwig_uploads/chrombpnet/dnase_prepare.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,115 @@ | ||
| import os | ||
| import json | ||
| import pandas as pd | ||
| import pybedtools | ||
|
|
||
| #encids = ["K562", "HEPG2", "IMR90", "H1ESC", "GM12878"] | ||
| #encids = ["K562", "HEPG2"] | ||
| encids = ["K562", "HEPG2", "IMR90_new", "H1ESC_new", "GM12878_new"] | ||
|
|
||
| encode_id = {"HEPG2": "ENCSR149XIL", | ||
| "K562": "ENCSR000EOT", | ||
| "IMR90_new": "ENCSR477RTP", | ||
| "GM12878_new": "ENCSR000EMT", | ||
| "H1ESC_new": "ENCSR000EMU"} | ||
| odir='dnase/' | ||
| def make_bb_file(in_bed, out_bb): | ||
| assert(os.path.isfile("atac_temp.bed")==False) | ||
| command = "zcat "+in_bed+" | LC_COLLATE=C sort -k1,1 -k2,2n > atac_temp.bed" | ||
| print(command) | ||
| os.system(command) | ||
|
|
||
| command = "bedToBigBed atac_temp.bed /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/reference/chrom.sizes "+out_bb | ||
| print(command) | ||
| os.system(command) | ||
|
|
||
|
|
||
| command = "rm atac_temp.bed" | ||
| print(command) | ||
| os.system(command) | ||
|
|
||
| chrs = list(map(str,list(range(1,23)))) | ||
| chrs = ['chr'+i for i in chrs] | ||
| chrs = chrs + ['chrX', 'chrY'] | ||
|
|
||
| def make_sel_bedfile(in_bed, out_bed): | ||
| input_bed = pd.read_csv(in_bed, sep="\t", header=None) | ||
| print(input_bed.shape) | ||
| input_bed = input_bed[input_bed[0].isin(chrs)] | ||
| print(input_bed.shape) | ||
|
|
||
| input_bed[1] = input_bed[1]+input_bed[9]-500 | ||
| input_bed[2] = input_bed[1] + 1000 | ||
| print(input_bed.head()) | ||
| x = pybedtools.BedTool.from_dataframe(input_bed[[0,1,2]]) | ||
| x = x.sort().merge() | ||
| output_bed = x.to_dataframe() | ||
| print(output_bed.shape) | ||
| print(output_bed.head()) | ||
| output_bed.to_csv(out_bed, sep='\t', header=False, index=False) | ||
|
|
||
| for encid in encids: | ||
| print(encid) | ||
| ofile = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/DNASE/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.counts_scores_new_compressed.stats" | ||
| if os.path.isfile(ofile): | ||
| counts_bw = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/DNASE/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.counts_scores_new_compressed.bw" | ||
| else: | ||
| print(ofile) | ||
| ofile = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/DNASE/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.counts_scores.stats" | ||
| if os.path.isfile(ofile): | ||
| counts_bw = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/DNASE/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.counts_scores.bw" | ||
| else: | ||
| counts_bw = None | ||
| print(ofile) | ||
| continue | ||
|
|
||
|
|
||
| ofile = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/DNASE/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.profile_scores_new_compressed.stats" | ||
| if os.path.isfile(ofile): | ||
| profile_bw = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/DNASE/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.profile_scores_new_compressed.bw" | ||
| else: | ||
| print(ofile) | ||
| ofile = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/DNASE/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.profile_scores.stats" | ||
| if os.path.isfile(ofile): | ||
| profile_bw = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/DNASE/"+encid+"/interpret_upload/average_preds/"+encid+"_folds_merged.profile_scores.bw" | ||
| else: | ||
| profile_bw = None | ||
| print(ofile) | ||
|
|
||
| continue | ||
|
|
||
| ofile = "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/DNASE/"+encid+"/interpret_upload/average_preds/per_folds.inputs.bed.gz" | ||
| if os.path.isfile(ofile): | ||
| sel_path = os.path.join("/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/DNASE/", encid+"/interpret_upload/average_preds/selected.regions.valid.merged.bed.gz" ) | ||
| sel_path_bb = os.path.join("/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/chrombpnet/folds/DNASE/", encid+"/interpret_upload/average_preds/selected.regions.valid.merged.bigBed" ) | ||
| if not os.path.isfile(sel_path): | ||
| make_sel_bedfile(ofile, sel_path) | ||
|
|
||
| if os.path.isfile(sel_path) and (not os.path.isfile(sel_path_bb)): | ||
| make_bb_file(sel_path, sel_path_bb) | ||
|
|
||
| else: | ||
| sel_path=None | ||
| sel_path_bb=None | ||
| print(ofile) | ||
| continue | ||
|
|
||
| assert(os.path.isfile(counts_bw)==True) | ||
| assert(os.path.isfile(profile_bw)==True) | ||
|
|
||
|
|
||
| output_json = {} | ||
| output_json["experiment"] = encode_id[encid] | ||
| output_json["counts sequence contribution scores bigWig"] = counts_bw | ||
| output_json["profile sequence contribution scores bigWig"] = profile_bw | ||
|
|
||
| if os.path.isfile(sel_path_bb): | ||
| output_json["selected regions for predicted signal and sequence contribution scores bigBed"] = sel_path_bb | ||
|
|
||
| if os.path.isfile(sel_path): | ||
| output_json["selected regions for predicted signal and sequence contribution scores bed"] = sel_path | ||
|
|
||
| if not os.path.isfile(odir+encode_id[encid]+".json"): | ||
| f = open(odir+encode_id[encid]+".json", "w") | ||
| json.dump(output_json, f, indent=4) | ||
| f.close() |
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