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zycE54OVwYX3eY;9=)Wqhx-6?|-wyV0)0JBP8N1!!cnv$cFN%9GRnB#SNRxu+S9 z!C{?sK6NHshH1L(^?DoOK)oLQH}2H)vr2?^i=*&n_V1_qWid$GROb=_5uDqIx6V?pqtZqb$e_ zHmG^pmhCd;u{uO2ujg4cvjHS4j3cUdP*#1@CE{)y_lV4Q;*Otk9;PF0-2O&|IEYAm zki@4>sAcwPk8_C+k(RWhhRw4i_RxD1{Lh2+IjR38yHaD@4AYe-Rf zR8JrOuaM_L^*TAO*H7+J3mxaBcwKjatUv)9YJj=^8b;*F6=QM#CSRIiF(UIRiLQ^+ z)b$Au@oot1kJ<@-_1G2x5moit2IuGbjsJ*q-_4@M4gU5F_SC;i$^GkZ&e$_&ioQzUq zb+ItWf)@c+rrgk+eDVBFUS$O>+1}=bvEM)!KjMp=oq$kF-=$OHF5GD+VHf`;K>KKE zJ(&cJ0(1RuQ7VmG9$g)o8aXpEJqm>8$ Date: Thu, 23 Jan 2020 15:57:26 +0100 Subject: [PATCH 2/3] only start xi on mgf-files and only if they don't start with 'recal_' --- mass_recal.py | 12 ++++++++++-- mass_recal_ms2.py | 12 ++++++++++-- preprocessing.py | 2 +- preprocessing_ms2recal.py | 2 +- 4 files changed, 22 insertions(+), 6 deletions(-) diff --git a/mass_recal.py b/mass_recal.py index 77db412..b230b8a 100755 --- a/mass_recal.py +++ b/mass_recal.py @@ -34,7 +34,15 @@ def run_xi_lin(peakfile, fasta, cnf, outpath, xipath, threads='1'): def get_ppm_error(xi_df, outfile): - xi_df = xi_df[(xi_df.decoy == 0) & (xi_df['match score'] > 6)] # TODO: new xi version requires lower score? + score_cutoff = 2 + xi_df = xi_df[(xi_df.decoy == 0) & (xi_df['match score'] > score_cutoff)] + xi_df_decoy = xi_df[(xi_df.decoy == 1) & (xi_df['match score'] > score_cutoff)] + + while (len(xi_df_decoy.index)>0.10*len(xi_df.index)) + score_cutoff=min(xi_df['match score'][xi_df['match score'] > score_cutoff]); + xi_df = xi_df[(xi_df.decoy == 0) & (xi_df['match score'] > score_cutoff)] + xi_df_decoy = xi_df[(xi_df.decoy == 1) & (xi_df['match score'] > score_cutoff)] + median_err = np.median(xi_df['Precoursor Error']) try: @@ -134,7 +142,7 @@ def main(mgf, fasta, xi_cnf, outpath, threads, xi_jar='./resources/XiSearch_1.6. fasta = '//130.149.167.198/rappsilbergroup/users/MitoProject/For Swantje/20170109_uniprot_mitoIDrun_FASTA.fasta' outpath = base_dir + '/error_shift' for in_file in os.listdir(mgf_dir): - if '.mgf' in in_file: + if in_file.endswith('.mgf') and not in_file.startswith('recal_') : main(mgf=os.path.join(mgf_dir, in_file), fasta=fasta, xi_cnf='D:/user/Swantje/projects/pipeline_prepro_xi_fdr/resources/xi_linear_by_tryp.conf', diff --git a/mass_recal_ms2.py b/mass_recal_ms2.py index 0e98881..f496fe0 100755 --- a/mass_recal_ms2.py +++ b/mass_recal_ms2.py @@ -35,7 +35,15 @@ def run_xi_lin(peakfile, fasta, cnf, outpath, xipath, threads='1'): def get_ppm_error(xi_df, peaks_df, outfile): - xi_df = xi_df[(xi_df.decoy == 0) & (xi_df['match score'] > 6)] + score_cutoff = 2 + xi_df = xi_df[(xi_df.decoy == 0) & (xi_df['match score'] > score_cutoff)] + xi_df_decoy = xi_df[(xi_df.decoy == 1) & (xi_df['match score'] > score_cutoff)] + + while (len(xi_df_decoy.index)>0.10*len(xi_df.index)): + score_cutoff=min(xi_df['match score'][xi_df['match score'] > score_cutoff]); + xi_df = xi_df[(xi_df.decoy == 0) & (xi_df['match score'] > score_cutoff)] + xi_df_decoy = xi_df[(xi_df.decoy == 1) & (xi_df['match score'] > score_cutoff)] + median_err = np.median(xi_df['Precoursor Error']) try: fig, ax = plt.subplots() @@ -156,7 +164,7 @@ def main(mgf, fasta, xi_cnf, outpath, threads, xi_jar='./resources/XiSearch_1.6. fasta = '//130.149.167.198/rappsilbergroup/users/MitoProject/For Swantje/20170109_uniprot_mitoIDrun_FASTA.fasta' outpath = base_dir + '/error_shift' for in_file in os.listdir(mgf_dir): - if '.mgf' in in_file: + if in_file.endswith('.mgf') and not in_file.startswith('recal_'): main(mgf=os.path.join(mgf_dir, in_file), fasta=fasta, xi_cnf='D:/user/Swantje/projects/pipeline_prepro_xi_fdr/resources/xi_linear_by_tryp.conf', diff --git a/preprocessing.py b/preprocessing.py index 6ae04b3..bdf25d0 100755 --- a/preprocessing.py +++ b/preprocessing.py @@ -300,7 +300,7 @@ def process_file(filepath, outdir, mscon_settings, split_acq, detector_filter, m pool.close() pool.join() - recal_in = [os.path.join(outdir, x) for x in os.listdir(outdir) if '.mgf' in x] + recal_in = [os.path.join(outdir, x) for x in os.listdir(outdir) if x.endswith('.mgf') and not x.startswith('recal_')] if recal: # pool = Pool(processes=nthr) if not os.path.exists(outdir): diff --git a/preprocessing_ms2recal.py b/preprocessing_ms2recal.py index 558e25a..49c02c4 100755 --- a/preprocessing_ms2recal.py +++ b/preprocessing_ms2recal.py @@ -300,7 +300,7 @@ def process_file(filepath, outdir, mscon_settings, split_acq, detector_filter, m pool.close() pool.join() - recal_in = [os.path.join(outdir, x) for x in os.listdir(outdir) if '.mgf' in x] + recal_in = [os.path.join(outdir, x) for x in os.listdir(outdir) if x.endswith('.mgf') and not x.startswith('recal_')] if recal: # pool = Pool(processes=nthr) if not os.path.exists(outdir): From 39e6c632c443aa88ac7eccae7632e8394b3ea265 Mon Sep 17 00:00:00 2001 From: lfischer Date: Thu, 23 Jan 2020 16:02:24 +0100 Subject: [PATCH 3/3] reduced the maxfdr to 2% again --- mass_recal.py | 2 +- mass_recal_ms2.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/mass_recal.py b/mass_recal.py index b230b8a..f690518 100755 --- a/mass_recal.py +++ b/mass_recal.py @@ -38,7 +38,7 @@ def get_ppm_error(xi_df, outfile): xi_df = xi_df[(xi_df.decoy == 0) & (xi_df['match score'] > score_cutoff)] xi_df_decoy = xi_df[(xi_df.decoy == 1) & (xi_df['match score'] > score_cutoff)] - while (len(xi_df_decoy.index)>0.10*len(xi_df.index)) + while (len(xi_df_decoy.index)>0.02*len(xi_df.index)) score_cutoff=min(xi_df['match score'][xi_df['match score'] > score_cutoff]); xi_df = xi_df[(xi_df.decoy == 0) & (xi_df['match score'] > score_cutoff)] xi_df_decoy = xi_df[(xi_df.decoy == 1) & (xi_df['match score'] > score_cutoff)] diff --git a/mass_recal_ms2.py b/mass_recal_ms2.py index f496fe0..f33bfc7 100755 --- a/mass_recal_ms2.py +++ b/mass_recal_ms2.py @@ -39,7 +39,7 @@ def get_ppm_error(xi_df, peaks_df, outfile): xi_df = xi_df[(xi_df.decoy == 0) & (xi_df['match score'] > score_cutoff)] xi_df_decoy = xi_df[(xi_df.decoy == 1) & (xi_df['match score'] > score_cutoff)] - while (len(xi_df_decoy.index)>0.10*len(xi_df.index)): + while (len(xi_df_decoy.index)>0.02*len(xi_df.index)): score_cutoff=min(xi_df['match score'][xi_df['match score'] > score_cutoff]); xi_df = xi_df[(xi_df.decoy == 0) & (xi_df['match score'] > score_cutoff)] xi_df_decoy = xi_df[(xi_df.decoy == 1) & (xi_df['match score'] > score_cutoff)]