From 26a7faea1abc59ec44bff59a78c7dfe047497871 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Tue, 9 Jan 2024 16:46:58 +0100 Subject: [PATCH 01/27] add main script --- msannika_fdr.py | 219 ++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 219 insertions(+) create mode 100644 msannika_fdr.py diff --git a/msannika_fdr.py b/msannika_fdr.py new file mode 100644 index 0000000..fe5db5b --- /dev/null +++ b/msannika_fdr.py @@ -0,0 +1,219 @@ +#!/usr/bin/env python3 + +# MS ANNIKA FDR VALIDATOR +# 2024 (c) Micha Johannes Birklbauer +# https://github.com/michabirklbauer/ +# micha.birklbauer@gmail.com + +# version tracking +__version = "1.0.0" +__date = "2024-01-09" + +# REQUIREMENTS +# pip install pandas +# pip install openpyxl + +###################### + +# import packages +import argparse +import pandas as pd + +class MSAnnika_CSM_Grouper: + + @staticmethod + def get_crosslink_key(row: pd.Series) -> str: + a = str(row["Sequence A"]) + str(row["Crosslinker Position A"]) + b = str(row["Sequence B"]) + str(row["Crosslinker Position B"]) + return "-".join(sorted([a, b])) + + @staticmethod + def get_nr_proteins(row: pd.Series) -> int: + proteins_str = row["Accession A"].strip(";") + ";" + row["Accession B"].strip(";") + return len(proteins_str.split(";")) + + @staticmethod + def get_best_csm_score(csms: List[pd.Series]) -> float: + + best_score = 0 + + for csm in csms: + if csm["Combined Score"] > best_score: + best_score = csm["Combined Score"] + + return best_score + + @staticmethod + def get_decoy_flag(row: pd.Series) -> bool: + return True if "D" in row["Alpha T/D"] or "D" in row["Beta T/D"] else False + + @staticmethod + def group(data: pd.DataFrame) -> pd.DataFrame: + + crosslinks = dict() + + for i, row in data.iterrows(): + crosslink = get_crosslink_key(row) + if crosslink in crosslinks: + crosslinks[crosslink].append(row) + else: + crosslinks[crosslink] = [row] + + rows = list() + columns = ["CHECKED", + "Crosslinker", + "Crosslink Type", + "# CSMs", + "# Proteins", + "Sequence A", + "Accession A", + "Position A", + "Sequence B", + "Accession B", + "Position B", + "Protein Descriptions A", + "Protein Descriptions B", + "Best CSM Score", + "In protein A", + "In protein B", + "Decoy", + "Modifications A", + "Modifications B", + "Confidence"] + + for crosslink in crosslinks: + row = pd.Series({"CHECKED": False, + "Crosslinker": crosslinks[crosslink][0]["Crosslinker"], + "Crosslink Type": crosslinks[crosslink][0]["Crosslink Type"], + "# CSMs": len(crosslinks[crosslink]), + "# Proteins": MSAnnika_CSM_Grouper.get_nr_proteins(crosslinks[crosslink][0]), + "Sequence A": crosslinks[crosslink][0]["Sequence A"], + "Accession A": crosslinks[crosslink][0]["Accession A"], + "Position A": crosslinks[crosslink][0]["Crosslinker Position A"], + "Sequence B": crosslinks[crosslink][0]["Sequence B"], + "Accession B": crosslinks[crosslink][0]["Accession B"], + "Position B": crosslinks[crosslink][0]["Crosslinker Position B"], + "Protein Descriptions A": crosslinks[crosslink][0]["Accession A"], + "Protein Descriptions B": crosslinks[crosslink][0]["Accession B"], + "Best CSM Score": MSAnnika_CSM_Grouper.get_best_csm_score(crosslinks[crosslink]), + "In protein A": crosslinks[crosslink][0]["A in protein"], + "In protein B": crosslinks[crosslink][0]["B in protein"], + "Decoy": MSAnnika_CSM_Grouper.get_decoy_flag(crosslinks[crosslink][0]), + "Modifications A": crosslinks[crosslink][0]["Modifications A"], + "Modifications B": crosslinks[crosslink][0]["Modifications B"], + "Confidence": "Low"}) + rows.append(row) + + return pd.concat(rows, ignore_index = True, axis = 1, names = columns).T + +class MSAnnika_CSM_Validator: + + @staticmethod + def get_class(row: pd.Series) -> str: + return "Decoy" if "D" in row["Alpha T/D"] or "D" in row["Beta T/D"] else "Target" + + @staticmethod + def get_fdr(data: pd.DataFrame, score: float) -> float: + + df = data[data["Combined Score"] > score] + df["Class"] = filtered_df.apply(lambda row: MSAnnika_CSM_Validator.get_class(row), axis = 1) + + return df[df["Class"] == "Decoy"].shape[0] / df[df["Class"] == "Target"].shape[0] + + @staticmethod + def get_cutoff(data: pd.DataFrame, fdr: float) -> float: + + scores = sorted(data["Combined Score"].tolist()) + for score in scores: + if MSAnnika_CSM_Validator.get_fdr(data, score) < fdr: + return score + + return scores[0] + + @staticmethod + def validate(data: pd.DataFrame, fdr: float) -> pd.DataFrame: + + cutoff = MSAnnika_CSM_Validator.get_cutoff(data, fdr) + df = data[data["Combined Score"] > cutoff] + + if "Confidence" not in df.columns: + return df + + df["Confidence"] = "High" + + return df + +class MSAnnika_Crosslink_Validator: + + @staticmethod + def get_class(row: pd.Series) -> str: + return "Decoy" if row["Decoy"] else "Target" + + @staticmethod + def get_fdr(data: pd.DataFrame, score: float) -> float: + + df = data[data["Best CSM Score"] > score] + df["Class"] = filtered_df.apply(lambda row: MSAnnika_Crosslink_Validator.get_class(row), axis = 1) + + return df[df["Class"] == "Decoy"].shape[0] / df[df["Class"] == "Target"].shape[0] + + @staticmethod + def get_cutoff(data: pd.DataFrame, fdr: float) -> float: + + scores = sorted(data["Best CSM Score"].tolist()) + for score in scores: + if MSAnnika_Crosslink_Validator.get_fdr(data, score) < fdr: + return score + + return scores[0] + + @staticmethod + def validate(data: pd.DataFrame, fdr: float) -> pd.DataFrame: + + cutoff = MSAnnika_Crosslink_Validator.get_cutoff(data, fdr) + df = data[data["Best CSM Score"] > cutoff] + df["Confidence"] = "High" + + return df + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument(metavar = "f", + dest = "files", + help = "Name/Path of the MS Annika result files to process.", + type = str, + nargs = "+") + parser.add_argument("-fdr", "--false_discovery_rate", + dest = "fdr", + default = None, + help = "FDR for CSM/crosslink validation.", + type = float) + parser.add_argument("--version", + action = "version", + version = __version) + args = parser.parse_args() + + for f, file in enumerate(args.files): + df = pd.read_excel(file) + + if "Combined Score" in df.columns: + crosslinks = MSAnnika_CSM_Grouper.group(df) + crosslinks.to_excel(file.rstrip(".xlsx") + "_crosslinks.xlsx", sheet_name = "Crosslinks", index = False) + if args.fdr is not None: + validated_csms = MSAnnika_CSM_Validator.validate(df, args.fdr) + validated_csms.to_excel(file.rstrip(".xlsx") + "_validated.xlsx", sheet_name = "CSMs", index = False) + validated_crosslinks = MSAnnika_Crosslink_Validator.validate(crosslinks, args.fdr) + validated_crosslinks.to_excel(file.rstrip(".xlsx") + "_crosslinks_validated.xlsx", sheet_name = "Crosslinks", index = False) + else: + if args.fdr is not None: + validated_crosslinks = MSAnnika_Crosslink_Validator.validate(df, args.fdr) + validated_crosslinks.to_excel(file.rstrip(".xlsx") + "_validated.xlsx", sheet_name = "Crosslinks", index = False) + else: + print("Crosslink file without FDR given. Nothing to do.") + + print(f"Processed {f + 1} files...") + + print("Done!") + +if __name__ == "__main__": + main() From 8ecbe94db255a815201a0943cd55b49a276cd689 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Tue, 9 Jan 2024 16:47:47 +0100 Subject: [PATCH 02/27] add sample data --- data/DSSO_CSMs.xlsx | Bin 0 -> 842196 bytes data/DSSO_Crosslinks.xlsx | Bin 0 -> 208072 bytes 2 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 data/DSSO_CSMs.xlsx create mode 100644 data/DSSO_Crosslinks.xlsx diff --git a/data/DSSO_CSMs.xlsx b/data/DSSO_CSMs.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..9c1616098c41a8e575ecb9d6cc4ebd39e34c1df6 GIT binary patch literal 842196 zcmbTc1ytP4(l>~^yTf3?83uQEf+n~P8rbk0ZgnOY420zRSnR z+1%EJo$a5`|2Ns3wLyeL|B;`&xwDIvgS{{{2OE%@%G}=6!OY6uQkdG!)q<6eT2w?x z-P{)J`o6;Di?c6JxjFXnb&7d8h+bNlySEF7Hez^?C8XG?ZR zu&E8$(wrRx1oE)IpXR^!p#IN2sXlo*n*V><(ZRyP%G6xS!PL#p+}`#7VPp3HTtQ9s 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zg}~0c7LNzzy}|Np&m?&8JA|L<{Oj)ja-Ao`XxAA&YKXwW6ObdnAQ}6v;Rgvnas0ar vf9-pJ*5WHf{m=KrznlLxDgSJKOoaOHQnZOa&4Jx&wBYk3NC8m-Bn Date: Wed, 10 Jan 2024 17:13:57 +0100 Subject: [PATCH 03/27] add main function return --- msannika_fdr.py | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/msannika_fdr.py b/msannika_fdr.py index fe5db5b..ac0ec9c 100644 --- a/msannika_fdr.py +++ b/msannika_fdr.py @@ -176,7 +176,7 @@ def validate(data: pd.DataFrame, fdr: float) -> pd.DataFrame: return df -def main() -> None: +def main(argv = None) -> List[pd.DataFrame]: parser = argparse.ArgumentParser() parser.add_argument(metavar = "f", dest = "files", @@ -191,7 +191,9 @@ def main() -> None: parser.add_argument("--version", action = "version", version = __version) - args = parser.parse_args() + args = parser.parse_args(argv) + + result_list = list() for f, file in enumerate(args.files): df = pd.read_excel(file) @@ -199,21 +201,26 @@ def main() -> None: if "Combined Score" in df.columns: crosslinks = MSAnnika_CSM_Grouper.group(df) crosslinks.to_excel(file.rstrip(".xlsx") + "_crosslinks.xlsx", sheet_name = "Crosslinks", index = False) + result_list.append(crosslinks) if args.fdr is not None: validated_csms = MSAnnika_CSM_Validator.validate(df, args.fdr) validated_csms.to_excel(file.rstrip(".xlsx") + "_validated.xlsx", sheet_name = "CSMs", index = False) + result_list.append(validated_csms) validated_crosslinks = MSAnnika_Crosslink_Validator.validate(crosslinks, args.fdr) validated_crosslinks.to_excel(file.rstrip(".xlsx") + "_crosslinks_validated.xlsx", sheet_name = "Crosslinks", index = False) + result_list.append(validated_crosslinks) else: if args.fdr is not None: validated_crosslinks = MSAnnika_Crosslink_Validator.validate(df, args.fdr) validated_crosslinks.to_excel(file.rstrip(".xlsx") + "_validated.xlsx", sheet_name = "Crosslinks", index = False) + result_list.append(validated_crosslinks) else: - print("Crosslink file without FDR given. Nothing to do.") + print(f"Crosslink file without FDR given. Nothing to do. Skipping file {file}.") print(f"Processed {f + 1} files...") print("Done!") + return result_list if __name__ == "__main__": - main() + r = main() From ee67cdb06a58c1c0b8fbc619c89cdeac0a70f48c Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Wed, 10 Jan 2024 17:14:26 +0100 Subject: [PATCH 04/27] add requirements --- requirements.txt | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 requirements.txt diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..2f5b8d3 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,2 @@ +pandas +openpyxl \ No newline at end of file From 3a9e67736040e8f9efb40cae0d81263616bcc76c Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Wed, 10 Jan 2024 17:14:44 +0100 Subject: [PATCH 05/27] add gh-actions --- .github/workflows/python-app.yml | 45 ++++++++++++++++++++++++++++++++ tests/tests.py | 15 +++++++++++ 2 files changed, 60 insertions(+) create mode 100644 .github/workflows/python-app.yml create mode 100644 tests/tests.py diff --git a/.github/workflows/python-app.yml b/.github/workflows/python-app.yml new file mode 100644 index 0000000..bef7085 --- /dev/null +++ b/.github/workflows/python-app.yml @@ -0,0 +1,45 @@ +# This workflow will install Python dependencies, run tests and lint with a variety of Python versions +# Reference workflow provided by (c) GitHub +# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions + +name: msannika_fdr + +on: + push: + branches: [ master ] + pull_request: + branches: [ master ] + +jobs: + build: + + runs-on: ubuntu-latest + strategy: + matrix: + python-version: ['3.7', '3.8', '3.9', '3.10', '3.11', '3.12'] + + steps: + - uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v3 + with: + python-version: ${{ matrix.python-version }} + - name: Copy scripts and data to "/tests" + run: | + cp msannika_fdr.py tests + cp data/DSSO_Crosslinks.xlsx . + cp data/DSSO_CSMs.xlsx . + - name: Install dependencies + run: | + python -m pip install --upgrade pip + python -m pip install flake8 pytest + if [ -f requirements.txt ]; then pip install -r requirements.txt; fi + - name: Lint with flake8 + run: | + # stop the build if there are Python syntax errors or undefined names + flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics + # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide + flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics + - name: Test with pytest + run: | + pytest tests/tests.py diff --git a/tests/tests.py b/tests/tests.py new file mode 100644 index 0000000..63ca223 --- /dev/null +++ b/tests/tests.py @@ -0,0 +1,15 @@ +#!/usr/bin/env python3 + +# MS ANNIKA FDR VALIDATOR - TESTS +# 2024 (c) Micha Johannes Birklbauer +# https://github.com/michabirklbauer/ +# micha.birklbauer@gmail.com + +# test 1 +def test1_msannika_fdr(): + + from msannika_fdr import main + + result = main(["DSSO_CSMs.xlsx"]) + + assert True From dbfc2b969ddb060a29e1400c46e80257945be4ef Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Wed, 10 Jan 2024 17:19:49 +0100 Subject: [PATCH 06/27] typing imports --- msannika_fdr.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/msannika_fdr.py b/msannika_fdr.py index ac0ec9c..1408093 100644 --- a/msannika_fdr.py +++ b/msannika_fdr.py @@ -19,6 +19,8 @@ import argparse import pandas as pd +from typing import List + class MSAnnika_CSM_Grouper: @staticmethod From 733443ad1237cf5cd4038bdb39628303f0821233 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Wed, 10 Jan 2024 17:24:42 +0100 Subject: [PATCH 07/27] fix names --- msannika_fdr.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/msannika_fdr.py b/msannika_fdr.py index 1408093..d252c62 100644 --- a/msannika_fdr.py +++ b/msannika_fdr.py @@ -55,7 +55,7 @@ def group(data: pd.DataFrame) -> pd.DataFrame: crosslinks = dict() for i, row in data.iterrows(): - crosslink = get_crosslink_key(row) + crosslink = MSAnnika_CSM_Grouper.get_crosslink_key(row) if crosslink in crosslinks: crosslinks[crosslink].append(row) else: @@ -118,7 +118,7 @@ def get_class(row: pd.Series) -> str: def get_fdr(data: pd.DataFrame, score: float) -> float: df = data[data["Combined Score"] > score] - df["Class"] = filtered_df.apply(lambda row: MSAnnika_CSM_Validator.get_class(row), axis = 1) + df["Class"] = df.apply(lambda row: MSAnnika_CSM_Validator.get_class(row), axis = 1) return df[df["Class"] == "Decoy"].shape[0] / df[df["Class"] == "Target"].shape[0] @@ -155,7 +155,7 @@ def get_class(row: pd.Series) -> str: def get_fdr(data: pd.DataFrame, score: float) -> float: df = data[data["Best CSM Score"] > score] - df["Class"] = filtered_df.apply(lambda row: MSAnnika_Crosslink_Validator.get_class(row), axis = 1) + df["Class"] = df.apply(lambda row: MSAnnika_Crosslink_Validator.get_class(row), axis = 1) return df[df["Class"] == "Decoy"].shape[0] / df[df["Class"] == "Target"].shape[0] From b45b17f5069d8553978e9fa06e8c6ba83ae1f0c5 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Wed, 10 Jan 2024 17:29:11 +0100 Subject: [PATCH 08/27] enforce accession to str --- msannika_fdr.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/msannika_fdr.py b/msannika_fdr.py index d252c62..66eab29 100644 --- a/msannika_fdr.py +++ b/msannika_fdr.py @@ -31,7 +31,7 @@ def get_crosslink_key(row: pd.Series) -> str: @staticmethod def get_nr_proteins(row: pd.Series) -> int: - proteins_str = row["Accession A"].strip(";") + ";" + row["Accession B"].strip(";") + proteins_str = str(row["Accession A"]).strip(";") + ";" + str(row["Accession B"]).strip(";") return len(proteins_str.split(";")) @staticmethod From 46661ffb2efd4faeb7c771216127740fcd5d96a4 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Wed, 10 Jan 2024 17:42:14 +0100 Subject: [PATCH 09/27] set values pandas-style --- msannika_fdr.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/msannika_fdr.py b/msannika_fdr.py index 66eab29..466849d 100644 --- a/msannika_fdr.py +++ b/msannika_fdr.py @@ -141,7 +141,7 @@ def validate(data: pd.DataFrame, fdr: float) -> pd.DataFrame: if "Confidence" not in df.columns: return df - df["Confidence"] = "High" + df["Confidence"] = df.apply(lambda row: "High", axis = 1) return df @@ -174,7 +174,7 @@ def validate(data: pd.DataFrame, fdr: float) -> pd.DataFrame: cutoff = MSAnnika_Crosslink_Validator.get_cutoff(data, fdr) df = data[data["Best CSM Score"] > cutoff] - df["Confidence"] = "High" + df["Confidence"] = df.apply(lambda row: "High", axis = 1) return df From a7c1ffc2669703ca43dc0cc8c448d7dac2d48d44 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Wed, 10 Jan 2024 17:42:35 +0100 Subject: [PATCH 10/27] accept values greater 1.0 --- msannika_fdr.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/msannika_fdr.py b/msannika_fdr.py index 466849d..f2d8432 100644 --- a/msannika_fdr.py +++ b/msannika_fdr.py @@ -205,15 +205,15 @@ def main(argv = None) -> List[pd.DataFrame]: crosslinks.to_excel(file.rstrip(".xlsx") + "_crosslinks.xlsx", sheet_name = "Crosslinks", index = False) result_list.append(crosslinks) if args.fdr is not None: - validated_csms = MSAnnika_CSM_Validator.validate(df, args.fdr) + validated_csms = MSAnnika_CSM_Validator.validate(df, args.fdr if args.fdr < 1.0 else args.fdr / 100) validated_csms.to_excel(file.rstrip(".xlsx") + "_validated.xlsx", sheet_name = "CSMs", index = False) result_list.append(validated_csms) - validated_crosslinks = MSAnnika_Crosslink_Validator.validate(crosslinks, args.fdr) + validated_crosslinks = MSAnnika_Crosslink_Validator.validate(crosslinks, args.fdr if args.fdr < 1.0 else args.fdr / 100) validated_crosslinks.to_excel(file.rstrip(".xlsx") + "_crosslinks_validated.xlsx", sheet_name = "Crosslinks", index = False) result_list.append(validated_crosslinks) else: if args.fdr is not None: - validated_crosslinks = MSAnnika_Crosslink_Validator.validate(df, args.fdr) + validated_crosslinks = MSAnnika_Crosslink_Validator.validate(df, args.fdr if args.fdr < 1.0 else args.fdr / 100) validated_crosslinks.to_excel(file.rstrip(".xlsx") + "_validated.xlsx", sheet_name = "Crosslinks", index = False) result_list.append(validated_crosslinks) else: From e6848a9837c89253bca5035805c9d70e72a6e757 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 12:06:03 +0100 Subject: [PATCH 11/27] fix SettingWithCopyWarning --- msannika_fdr.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/msannika_fdr.py b/msannika_fdr.py index f2d8432..984c199 100644 --- a/msannika_fdr.py +++ b/msannika_fdr.py @@ -117,7 +117,7 @@ def get_class(row: pd.Series) -> str: @staticmethod def get_fdr(data: pd.DataFrame, score: float) -> float: - df = data[data["Combined Score"] > score] + df = data[data["Combined Score"] > score].copy() df["Class"] = df.apply(lambda row: MSAnnika_CSM_Validator.get_class(row), axis = 1) return df[df["Class"] == "Decoy"].shape[0] / df[df["Class"] == "Target"].shape[0] @@ -136,7 +136,7 @@ def get_cutoff(data: pd.DataFrame, fdr: float) -> float: def validate(data: pd.DataFrame, fdr: float) -> pd.DataFrame: cutoff = MSAnnika_CSM_Validator.get_cutoff(data, fdr) - df = data[data["Combined Score"] > cutoff] + df = data[data["Combined Score"] > cutoff].copy() if "Confidence" not in df.columns: return df @@ -154,7 +154,7 @@ def get_class(row: pd.Series) -> str: @staticmethod def get_fdr(data: pd.DataFrame, score: float) -> float: - df = data[data["Best CSM Score"] > score] + df = data[data["Best CSM Score"] > score].copy() df["Class"] = df.apply(lambda row: MSAnnika_Crosslink_Validator.get_class(row), axis = 1) return df[df["Class"] == "Decoy"].shape[0] / df[df["Class"] == "Target"].shape[0] @@ -173,7 +173,7 @@ def get_cutoff(data: pd.DataFrame, fdr: float) -> float: def validate(data: pd.DataFrame, fdr: float) -> pd.DataFrame: cutoff = MSAnnika_Crosslink_Validator.get_cutoff(data, fdr) - df = data[data["Best CSM Score"] > cutoff] + df = data[data["Best CSM Score"] > cutoff].copy() df["Confidence"] = df.apply(lambda row: "High", axis = 1) return df From 9e3a7fc8e788cf0eb35abbe79c8f7449b69ea4f2 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 12:06:17 +0100 Subject: [PATCH 12/27] fdr type check and logging --- msannika_fdr.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/msannika_fdr.py b/msannika_fdr.py index 984c199..b6fa3c3 100644 --- a/msannika_fdr.py +++ b/msannika_fdr.py @@ -195,6 +195,9 @@ def main(argv = None) -> List[pd.DataFrame]: version = __version) args = parser.parse_args(argv) + if args.fdr is not None: + print(f"Using {float(args.fdr) if float(args.fdr) < 1.0 else float(args.fdr) / 100.0} FDR.") + result_list = list() for f, file in enumerate(args.files): @@ -205,10 +208,10 @@ def main(argv = None) -> List[pd.DataFrame]: crosslinks.to_excel(file.rstrip(".xlsx") + "_crosslinks.xlsx", sheet_name = "Crosslinks", index = False) result_list.append(crosslinks) if args.fdr is not None: - validated_csms = MSAnnika_CSM_Validator.validate(df, args.fdr if args.fdr < 1.0 else args.fdr / 100) + validated_csms = MSAnnika_CSM_Validator.validate(df, float(args.fdr) if float(args.fdr) < 1.0 else float(args.fdr) / 100.0) validated_csms.to_excel(file.rstrip(".xlsx") + "_validated.xlsx", sheet_name = "CSMs", index = False) result_list.append(validated_csms) - validated_crosslinks = MSAnnika_Crosslink_Validator.validate(crosslinks, args.fdr if args.fdr < 1.0 else args.fdr / 100) + validated_crosslinks = MSAnnika_Crosslink_Validator.validate(crosslinks, float(args.fdr) if float(args.fdr) < 1.0 else float(args.fdr) / 100.0) validated_crosslinks.to_excel(file.rstrip(".xlsx") + "_crosslinks_validated.xlsx", sheet_name = "Crosslinks", index = False) result_list.append(validated_crosslinks) else: From 25d3e2dfb4c6c809919780797b255d03e0eceab4 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 12:35:18 +0100 Subject: [PATCH 13/27] crosslink file input tests --- tests/tests.py | 20 ++++++++++++++++++-- 1 file changed, 18 insertions(+), 2 deletions(-) diff --git a/tests/tests.py b/tests/tests.py index 63ca223..9086934 100644 --- a/tests/tests.py +++ b/tests/tests.py @@ -5,11 +5,27 @@ # https://github.com/michabirklbauer/ # micha.birklbauer@gmail.com -# test 1 +# crosslink file without fdr should not do anything def test1_msannika_fdr(): from msannika_fdr import main result = main(["DSSO_CSMs.xlsx"]) - assert True + assert len(result) == 0 + +# crosslink file with fdr should validate +def test2_msannika_fdr(): + + from msannika_fdr import main + + result = main(["DSSO_CSMs.xlsx", "-fdr", "0.01"]) + + # check nr of results + assert len(result) == 1 + + # check nr of crosslinks + assert result[0].shape[0] == 714 + + # check fdr + assert result[0][result[0]["Decoy"] == False].shape[0] / result[0][result[0]["Decoy"] == True].shape[0] < 0.01 From 46f3a6c9904d0db148327f85e6ea3bf00b5c265a Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 13:06:27 +0100 Subject: [PATCH 14/27] proper filename handling --- msannika_fdr.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/msannika_fdr.py b/msannika_fdr.py index b6fa3c3..9e08116 100644 --- a/msannika_fdr.py +++ b/msannika_fdr.py @@ -205,19 +205,19 @@ def main(argv = None) -> List[pd.DataFrame]: if "Combined Score" in df.columns: crosslinks = MSAnnika_CSM_Grouper.group(df) - crosslinks.to_excel(file.rstrip(".xlsx") + "_crosslinks.xlsx", sheet_name = "Crosslinks", index = False) + crosslinks.to_excel(".xlsx".join(file.split(".xlsx")[:-1]) + "_crosslinks.xlsx", sheet_name = "Crosslinks", index = False) result_list.append(crosslinks) if args.fdr is not None: validated_csms = MSAnnika_CSM_Validator.validate(df, float(args.fdr) if float(args.fdr) < 1.0 else float(args.fdr) / 100.0) - validated_csms.to_excel(file.rstrip(".xlsx") + "_validated.xlsx", sheet_name = "CSMs", index = False) + validated_csms.to_excel(".xlsx".join(file.split(".xlsx")[:-1]) + "_validated.xlsx", sheet_name = "CSMs", index = False) result_list.append(validated_csms) validated_crosslinks = MSAnnika_Crosslink_Validator.validate(crosslinks, float(args.fdr) if float(args.fdr) < 1.0 else float(args.fdr) / 100.0) - validated_crosslinks.to_excel(file.rstrip(".xlsx") + "_crosslinks_validated.xlsx", sheet_name = "Crosslinks", index = False) + validated_crosslinks.to_excel(".xlsx".join(file.split(".xlsx")[:-1]) + "_crosslinks_validated.xlsx", sheet_name = "Crosslinks", index = False) result_list.append(validated_crosslinks) else: if args.fdr is not None: validated_crosslinks = MSAnnika_Crosslink_Validator.validate(df, args.fdr if args.fdr < 1.0 else args.fdr / 100) - validated_crosslinks.to_excel(file.rstrip(".xlsx") + "_validated.xlsx", sheet_name = "Crosslinks", index = False) + validated_crosslinks.to_excel(".xlsx".join(file.split(".xlsx")[:-1]) + "_validated.xlsx", sheet_name = "Crosslinks", index = False) result_list.append(validated_crosslinks) else: print(f"Crosslink file without FDR given. Nothing to do. Skipping file {file}.") From dd7515421cc1a9b4df972ad180586aab4030517d Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 13:06:49 +0100 Subject: [PATCH 15/27] fix tests --- tests/tests.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/tests.py b/tests/tests.py index 9086934..bac663b 100644 --- a/tests/tests.py +++ b/tests/tests.py @@ -10,7 +10,7 @@ def test1_msannika_fdr(): from msannika_fdr import main - result = main(["DSSO_CSMs.xlsx"]) + result = main(["DSSO_Crosslinks.xlsx"]) assert len(result) == 0 @@ -19,7 +19,7 @@ def test2_msannika_fdr(): from msannika_fdr import main - result = main(["DSSO_CSMs.xlsx", "-fdr", "0.01"]) + result = main(["DSSO_Crosslinks.xlsx", "-fdr", "0.01"]) # check nr of results assert len(result) == 1 From f7666c3826826ac8070b3671cc18a074d76df0a7 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 13:09:32 +0100 Subject: [PATCH 16/27] fix fdr calculation --- tests/tests.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/tests.py b/tests/tests.py index bac663b..94ebc93 100644 --- a/tests/tests.py +++ b/tests/tests.py @@ -28,4 +28,4 @@ def test2_msannika_fdr(): assert result[0].shape[0] == 714 # check fdr - assert result[0][result[0]["Decoy"] == False].shape[0] / result[0][result[0]["Decoy"] == True].shape[0] < 0.01 + assert result[0][result[0]["Decoy"] == True].shape[0] / result[0][result[0]["Decoy"] == False].shape[0] < 0.01 From ff281c24c88e11f0aba4691d214940fdd447f538 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 13:20:46 +0100 Subject: [PATCH 17/27] change confidence val --- msannika_fdr.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/msannika_fdr.py b/msannika_fdr.py index 9e08116..4d089ac 100644 --- a/msannika_fdr.py +++ b/msannika_fdr.py @@ -103,7 +103,7 @@ def group(data: pd.DataFrame) -> pd.DataFrame: "Decoy": MSAnnika_CSM_Grouper.get_decoy_flag(crosslinks[crosslink][0]), "Modifications A": crosslinks[crosslink][0]["Modifications A"], "Modifications B": crosslinks[crosslink][0]["Modifications B"], - "Confidence": "Low"}) + "Confidence": "Unknown"}) rows.append(row) return pd.concat(rows, ignore_index = True, axis = 1, names = columns).T From 0a95b61e0f5aba084a1355c9cf2f5c85c35a240a Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 13:25:22 +0100 Subject: [PATCH 18/27] add more tests --- tests/tests.py | 45 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 45 insertions(+) diff --git a/tests/tests.py b/tests/tests.py index 94ebc93..099655f 100644 --- a/tests/tests.py +++ b/tests/tests.py @@ -29,3 +29,48 @@ def test2_msannika_fdr(): # check fdr assert result[0][result[0]["Decoy"] == True].shape[0] / result[0][result[0]["Decoy"] == False].shape[0] < 0.01 + +# crosslink file with fdr should validate +def test3_msannika_fdr(): + + from msannika_fdr import main + + result = main(["DSSO_Crosslinks.xlsx", "-fdr", "1"]) + + # check nr of results + assert len(result) == 1 + + # check nr of crosslinks + assert result[0].shape[0] == 714 + + # check fdr + assert result[0][result[0]["Decoy"] == True].shape[0] / result[0][result[0]["Decoy"] == False].shape[0] < 0.01 + +# crosslink file with fdr should validate +def test4_msannika_fdr(): + + from msannika_fdr import main + + result = main(["DSSO_Crosslinks.xlsx", "-fdr", "0.05"]) + + # check nr of results + assert len(result) == 1 + + # check nr of crosslinks + assert result[0].shape[0] == 807 + + # check fdr + assert result[0][result[0]["Decoy"] == True].shape[0] / result[0][result[0]["Decoy"] == False].shape[0] < 0.05 + +# csms file without fdr should group +def test5_msannika_fdr(): + + from msannika_fdr import main + + result = main(["DSSO_CSMs.xlsx"]) + + # check nr of results + assert len(result) == 1 + + # check nr of grouped crosslinks + assert result[0].shape[0] == 3192 From 720d06900ebf5a57b0dcfe221701fcc64bb9787d Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 13:44:04 +0100 Subject: [PATCH 19/27] finalize tests --- tests/tests.py | 102 +++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 102 insertions(+) diff --git a/tests/tests.py b/tests/tests.py index 099655f..a785db1 100644 --- a/tests/tests.py +++ b/tests/tests.py @@ -74,3 +74,105 @@ def test5_msannika_fdr(): # check nr of grouped crosslinks assert result[0].shape[0] == 3192 + +# csms file with fdr should validate +def test6_msannika_fdr(): + + import pandas as pd + from msannika_fdr import main + from msannika_fdr import MSAnnika_CSM_Validator as csm_val + + result = main(["DSSO_CSMs.xlsx", "-fdr", "0.01"]) + + # check nr of results + assert len(result) == 3 + + #### crosslinks #### + + # check nr of grouped crosslinks + assert result[0].shape[0] == 3192 + + #### validated crosslinks #### + + # check nr of validated crosslinks + assert result[2].shape[0] == 714 + + # check fdr of validated crosslinks + assert result[2][result[2]["Decoy"] == True].shape[0] / result[2][result[2]["Decoy"] == False].shape[0] < 0.01 + + #### validated csms #### + + # check nr of validated csms + assert result[1].shape[0] == 3021 + + # check fdr of validated csms + results[1]["Class"] = pd.apply(lambda row: csm_val.get_class(row), axis = 1) + assert result[1][result[1]["Class"] == "Decoy"].shape[0] / result[1][result[1]["Class"] == "Target"].shape[0] < 0.01 + +# csms file with fdr should validate +def test7_msannika_fdr(): + + import pandas as pd + from msannika_fdr import main + from msannika_fdr import MSAnnika_CSM_Validator as csm_val + + result = main(["DSSO_CSMs.xlsx", "-fdr", "1"]) + + # check nr of results + assert len(result) == 3 + + #### crosslinks #### + + # check nr of grouped crosslinks + assert result[0].shape[0] == 3192 + + #### validated crosslinks #### + + # check nr of validated crosslinks + assert result[2].shape[0] == 714 + + # check fdr of validated crosslinks + assert result[2][result[2]["Decoy"] == True].shape[0] / result[2][result[2]["Decoy"] == False].shape[0] < 0.01 + + #### validated csms #### + + # check nr of validated csms + assert result[1].shape[0] == 3021 + + # check fdr of validated csms + results[1]["Class"] = pd.apply(lambda row: csm_val.get_class(row), axis = 1) + assert result[1][result[1]["Class"] == "Decoy"].shape[0] / result[1][result[1]["Class"] == "Target"].shape[0] < 0.01 + +# csms file with fdr should validate +def test8_msannika_fdr(): + + import pandas as pd + from msannika_fdr import main + from msannika_fdr import MSAnnika_CSM_Validator as csm_val + + result = main(["DSSO_CSMs.xlsx", "-fdr", "0.05"]) + + # check nr of results + assert len(result) == 3 + + #### crosslinks #### + + # check nr of grouped crosslinks + assert result[0].shape[0] == 3192 + + #### validated crosslinks #### + + # check nr of validated crosslinks + assert result[2].shape[0] == 807 + + # check fdr of validated crosslinks + assert result[2][result[2]["Decoy"] == True].shape[0] / result[2][result[2]["Decoy"] == False].shape[0] < 0.01 + + #### validated csms #### + + # check nr of validated csms + assert result[1].shape[0] == 3331 + + # check fdr of validated csms + results[1]["Class"] = pd.apply(lambda row: csm_val.get_class(row), axis = 1) + assert result[1][result[1]["Class"] == "Decoy"].shape[0] / result[1][result[1]["Class"] == "Target"].shape[0] < 0.01 From 3beefac391694ae5506fa36be2cc541dd434f27f Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 13:46:45 +0100 Subject: [PATCH 20/27] fix tests --- tests/tests.py | 9 +++------ 1 file changed, 3 insertions(+), 6 deletions(-) diff --git a/tests/tests.py b/tests/tests.py index a785db1..b5225f7 100644 --- a/tests/tests.py +++ b/tests/tests.py @@ -78,7 +78,6 @@ def test5_msannika_fdr(): # csms file with fdr should validate def test6_msannika_fdr(): - import pandas as pd from msannika_fdr import main from msannika_fdr import MSAnnika_CSM_Validator as csm_val @@ -106,13 +105,12 @@ def test6_msannika_fdr(): assert result[1].shape[0] == 3021 # check fdr of validated csms - results[1]["Class"] = pd.apply(lambda row: csm_val.get_class(row), axis = 1) + result[1]["Class"] = result[1].apply(lambda row: csm_val.get_class(row), axis = 1) assert result[1][result[1]["Class"] == "Decoy"].shape[0] / result[1][result[1]["Class"] == "Target"].shape[0] < 0.01 # csms file with fdr should validate def test7_msannika_fdr(): - import pandas as pd from msannika_fdr import main from msannika_fdr import MSAnnika_CSM_Validator as csm_val @@ -140,13 +138,12 @@ def test7_msannika_fdr(): assert result[1].shape[0] == 3021 # check fdr of validated csms - results[1]["Class"] = pd.apply(lambda row: csm_val.get_class(row), axis = 1) + result[1]["Class"] = result[1].apply(lambda row: csm_val.get_class(row), axis = 1) assert result[1][result[1]["Class"] == "Decoy"].shape[0] / result[1][result[1]["Class"] == "Target"].shape[0] < 0.01 # csms file with fdr should validate def test8_msannika_fdr(): - import pandas as pd from msannika_fdr import main from msannika_fdr import MSAnnika_CSM_Validator as csm_val @@ -174,5 +171,5 @@ def test8_msannika_fdr(): assert result[1].shape[0] == 3331 # check fdr of validated csms - results[1]["Class"] = pd.apply(lambda row: csm_val.get_class(row), axis = 1) + result[1]["Class"] = result[1].apply(lambda row: csm_val.get_class(row), axis = 1) assert result[1][result[1]["Class"] == "Decoy"].shape[0] / result[1][result[1]["Class"] == "Target"].shape[0] < 0.01 From 611a88cbf13e4847dabcd1c2ddf11799252e62e7 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 13:59:17 +0100 Subject: [PATCH 21/27] fix fdr --- tests/tests.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/tests.py b/tests/tests.py index b5225f7..a3dd53a 100644 --- a/tests/tests.py +++ b/tests/tests.py @@ -163,7 +163,7 @@ def test8_msannika_fdr(): assert result[2].shape[0] == 807 # check fdr of validated crosslinks - assert result[2][result[2]["Decoy"] == True].shape[0] / result[2][result[2]["Decoy"] == False].shape[0] < 0.01 + assert result[2][result[2]["Decoy"] == True].shape[0] / result[2][result[2]["Decoy"] == False].shape[0] < 0.05 #### validated csms #### @@ -172,4 +172,4 @@ def test8_msannika_fdr(): # check fdr of validated csms result[1]["Class"] = result[1].apply(lambda row: csm_val.get_class(row), axis = 1) - assert result[1][result[1]["Class"] == "Decoy"].shape[0] / result[1][result[1]["Class"] == "Target"].shape[0] < 0.01 + assert result[1][result[1]["Class"] == "Decoy"].shape[0] / result[1][result[1]["Class"] == "Target"].shape[0] < 0.05 From 0171bba9a259633bc07270f4c740d1b6f81152ee Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 16:06:39 +0100 Subject: [PATCH 22/27] documentation --- README.md | 151 +++++++++++++++++++++++++++++++++++++++++++++++- msannika_fdr.py | 26 ++++++++- 2 files changed, 175 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index ee4d5b1..42bc8c2 100644 --- a/README.md +++ b/README.md @@ -1 +1,150 @@ -# MSAnnika_FDR \ No newline at end of file +![workflow_state](https://github.com/hgb-bin-proteomics/MSAnnika_FDR/workflows/msannika_fdr/badge.svg) + +# MS Annika FDR + +A script and functions to group and validate [MS Annika](https://github.com/hgb-bin-proteomics/MSAnnika) +results. The main use case would be for re-validating results after filtering or +merging results from different MS Annika runs. + +## Usage + +- Install python 3.7+: [https://www.python.org/downloads/](https://www.python.org/downloads/) +- Install requirements: `pip install -r requirements.txt` +- Export MS Annika results from Proteome Discoverer to Microsoft Excel format. +- Run `python msannika_fdr.py filename.xlsx -fdr 0.01` (see below for more examples). +- The script may take a few minutes, depending on the number of CSMs/crosslinks to process. +- Done! + +## Examples + +`msannika_fdr.py` takes one positional and one flagged argument. The first +argument always has to be the filename(s) of the MS Annika result file(s). You +may specify any number of result files, keep in mind however that +`msannika_fdr.py` will process these files seperately, if you want to merge +several result files, check out [MS Annika Combine Results](https://github.com/hgb-bin-proteomics/MSAnnika_Combine_Results). +For demonstration purposes we will use the files supplied in the `/data` folder. +`DSSO_Crosslinks.xlsx` contains unvalidated crosslinks from an MS Annika search, +`DSSO_CSMs.xlsx` contains unvalidated CSMs from an MS Annika search. + +The following is a valid `msannika_fdr.py` call: + +```bash +python msannika_fdr.py DSSO_Crosslinks.xlsx +``` + +This will not do anything because no FDR was given. You should see in the output +that the script skipped the file. However, doing the same with a CSM file +results in a different output: + +```bash +python msannika_fdr.py DSSO_CSMs.xlsx +``` + +This will group the CSMs by sequence and position to crosslinks and you should +see a file `DSSO_CSMs_crosslinks.xlsx` generated. + +If you suppy the argument `-fdr` or `--false_discovery_rate` and the desired FDR +as a floating point number, the results will be validated: + +```bash +python msannika_fdr.py DSSO_Crosslinks.xlsx -fdr 0.01 +``` + +This will validate the input crosslinks for estimated 1% FDR and will generate a +a file called `DSSO_Crosslinks_validated.xlsx` containing only crosslinks above +the estimated 1% FDR threshold. Note that the following command will produce the +same output: + +```bash +python msannika_fdr.py DSSO_Crosslinks.xlsx -fdr 1 +``` + +Validating a CSMs file works the same way: + +```bash +python msannika_fdr.py DSSO_CSMs.xlsx -fdr 0.01 +``` + +This will will validate the input CSMs for estimated 1% FDR and will generate a +a file `DSSO_CSMs_validated.xlsx` containing only CSMs above the estimated 1% +FDR threshold. Furthermore, it will group the input CSMs to crosslinks and +output them to the file `DSSO_CSMs_crosslinks.xlsx` and the validate those +crosslinks for 1% estimated FDR and store the result in +`DSSO_CSMs_crosslinks_validated.xlsx` + +You can also supply several files to the script like this: + +```bash +python msannika_fdr.py DSSO_CSMs.xlsx DSSO_Crosslinks.xlsx -fdr 0.01 +``` + +This will process the input files seperately and sequentially and produce the +as mentioned above: +- `DSSO_Crosslinks_validated.xlsx` +- `DSSO_CSMs_validated.xlsx` +- `DSSO_CSMs_crosslinks.xlsx` +- `DSSO_CSMs_crosslinks_validated.xlsx` + +## Parameters + +```python +""" +DESCRIPTION: +A script to group and validate results from MS Annika searches. +USAGE: +msannika_fdr.py f [f ...] + [-fdr FDR][--false_discovery_rate FDR] + [-h][--help] + [--version] +positional arguments: + f MS Annika result files in Microsoft Excel format (.xlsx) + to process. +optional arguments: + -fdr FDR, --false_discovery_rate FDR + False discovery rate to validate results for. Supports + both percentage input (e.g. 1) or fraction input (e.g. + 0.01). By default not set and the input results will + just be grouped to crosslinks (if CSMs as input) or + nothing will be done (if crosslinks as input). + Default: None + -h, --help show this help message and exit + --version show program's version number and exit +""" +``` + +## Known Issues + +[List of known issues](https://github.com/hgb-bin-proteomics/MSAnnika_FDR/issues) + +## Citing + +If you are using the MS Annika FDR script please cite: +``` +MS Annika 2.0 Identifies Cross-Linked Peptides in MS2–MS3-Based Workflows at High Sensitivity and Specificity +Micha J. Birklbauer, Manuel Matzinger, Fränze Müller, Karl Mechtler, and Viktoria Dorfer +Journal of Proteome Research 2023 22 (9), 3009-3021 +DOI: 10.1021/acs.jproteome.3c00325 +``` + +If you are using MS Annika please cite: +``` +MS Annika 2.0 Identifies Cross-Linked Peptides in MS2–MS3-Based Workflows at High Sensitivity and Specificity +Micha J. Birklbauer, Manuel Matzinger, Fränze Müller, Karl Mechtler, and Viktoria Dorfer +Journal of Proteome Research 2023 22 (9), 3009-3021 +DOI: 10.1021/acs.jproteome.3c00325 +``` +or +``` +MS Annika: A New Cross-Linking Search Engine +Georg J. Pirklbauer, Christian E. Stieger, Manuel Matzinger, Stephan Winkler, Karl Mechtler, and Viktoria Dorfer +Journal of Proteome Research 2021 20 (5), 2560-2569 +DOI: 10.1021/acs.jproteome.0c01000 +``` + +## License + +- [MIT](https://github.com/hgb-bin-proteomics/MSAnnika_FDR/blob/master/LICENSE) + +## Contact + +- [micha.birklbauer@fh-hagenberg.at](mailto:micha.birklbauer@fh-hagenberg.at) diff --git a/msannika_fdr.py b/msannika_fdr.py index 4d089ac..a0d3e4a 100644 --- a/msannika_fdr.py +++ b/msannika_fdr.py @@ -15,7 +15,31 @@ ###################### -# import packages +""" +DESCRIPTION: +A script to group and validate results from MS Annika searches. +USAGE: +msannika_fdr.py f [f ...] + [-fdr FDR][--false_discovery_rate FDR] + [-h][--help] + [--version] +positional arguments: + f MS Annika result files in Microsoft Excel format (.xlsx) + to process. +optional arguments: + -fdr FDR, --false_discovery_rate FDR + False discovery rate to validate results for. Supports + both percentage input (e.g. 1) or fraction input (e.g. + 0.01). By default not set and the input results will + just be grouped to crosslinks (if CSMs as input) or + nothing will be done (if crosslinks as input). + Default: None + -h, --help show this help message and exit + --version show program's version number and exit +""" + +###################### + import argparse import pandas as pd From c2e953a832c4370cbedbbc9d6c946887e6794505 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 16:22:17 +0100 Subject: [PATCH 23/27] add function documentation --- README.md | 45 ++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 42 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 42bc8c2..7ba4dea 100644 --- a/README.md +++ b/README.md @@ -17,7 +17,7 @@ merging results from different MS Annika runs. ## Examples -`msannika_fdr.py` takes one positional and one flagged argument. The first +`msannika_fdr.py` takes one positional and one optional argument. The first argument always has to be the filename(s) of the MS Annika result file(s). You may specify any number of result files, keep in mind however that `msannika_fdr.py` will process these files seperately, if you want to merge @@ -43,8 +43,8 @@ python msannika_fdr.py DSSO_CSMs.xlsx This will group the CSMs by sequence and position to crosslinks and you should see a file `DSSO_CSMs_crosslinks.xlsx` generated. -If you suppy the argument `-fdr` or `--false_discovery_rate` and the desired FDR -as a floating point number, the results will be validated: +If you suppy the optional argument `-fdr` or `--false_discovery_rate` and the +desired FDR as a floating point number, the results will be validated: ```bash python msannika_fdr.py DSSO_Crosslinks.xlsx -fdr 0.01 @@ -112,6 +112,45 @@ optional arguments: """ ``` +## Function Documentation + +If you want to integrate the MS Annika FDR calculation into your own scripts, +you can import the following functions as given: + +```python +import pandas as pd + +crosslinks = pd.read_excel("DSSO_Crosslinks.xlsx") +csms = pd.read_excel("DSSO_CSMs.xlsx") + +# Grouping CSMs to crosslinks +from msannika_fdr import MSAnnika_CSM_Grouper +Crosslinks_grouped_from_CSMs = MSAnnika_CSM_Grouper.group(csms) + +# The function signature of MSAnnika_CSM_Grouper.group is: +def group(data: pd.DataFrame) -> pd.DataFrame: + """code omitted""" + return + +# Validating CSMs for 0.01 FDR +from msannika_fdr import MSAnnika_CSM_Validator +Validated_CSMs = MSAnnika_CSM_Validator.validate(csms, 0.01) + +# The function signature of MSAnnika_CSM_Validator.validate is: +def validate(data: pd.DataFrame, fdr: float) -> pd.DataFrame: + """code omitted""" + return + +# Validating Crosslinks for 0.01 FDR +from msannika_fdr import MSAnnika_Crosslink_Validator +Validated_Crosslinks = MSAnnika_Crosslink_Validator.validate(crosslinks, 0.01) + +# The function signature of MSAnnika_Crosslink_Validator.validate is: +def validate(data: pd.DataFrame, fdr: float) -> pd.DataFrame: + """code omitted""" + return +``` + ## Known Issues [List of known issues](https://github.com/hgb-bin-proteomics/MSAnnika_FDR/issues) From 63c021e57d6713d5986b739b2087c7001580e4da Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 16:25:01 +0100 Subject: [PATCH 24/27] formatting --- README.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 7ba4dea..9064fae 100644 --- a/README.md +++ b/README.md @@ -22,9 +22,10 @@ argument always has to be the filename(s) of the MS Annika result file(s). You may specify any number of result files, keep in mind however that `msannika_fdr.py` will process these files seperately, if you want to merge several result files, check out [MS Annika Combine Results](https://github.com/hgb-bin-proteomics/MSAnnika_Combine_Results). -For demonstration purposes we will use the files supplied in the `/data` folder. -`DSSO_Crosslinks.xlsx` contains unvalidated crosslinks from an MS Annika search, -`DSSO_CSMs.xlsx` contains unvalidated CSMs from an MS Annika search. +For demonstration purposes we will use the files supplied in the `/data` folder: +- `DSSO_Crosslinks.xlsx` contains unvalidated crosslinks from an MS Annika +search. +- `DSSO_CSMs.xlsx` contains unvalidated CSMs from an MS Annika search. The following is a valid `msannika_fdr.py` call: From f0d7df762a8c897bc34e489203dfed8460e16757 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 16:27:00 +0100 Subject: [PATCH 25/27] clarification --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 9064fae..17902fc 100644 --- a/README.md +++ b/README.md @@ -54,7 +54,7 @@ python msannika_fdr.py DSSO_Crosslinks.xlsx -fdr 0.01 This will validate the input crosslinks for estimated 1% FDR and will generate a a file called `DSSO_Crosslinks_validated.xlsx` containing only crosslinks above the estimated 1% FDR threshold. Note that the following command will produce the -same output: +same output (values >= 1 will automatically divided by 100): ```bash python msannika_fdr.py DSSO_Crosslinks.xlsx -fdr 1 From 11f220bc7d4cf60f137f4e24f6c0cb50351bb929 Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 16:27:41 +0100 Subject: [PATCH 26/27] grammar --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 17902fc..60864b7 100644 --- a/README.md +++ b/README.md @@ -54,7 +54,7 @@ python msannika_fdr.py DSSO_Crosslinks.xlsx -fdr 0.01 This will validate the input crosslinks for estimated 1% FDR and will generate a a file called `DSSO_Crosslinks_validated.xlsx` containing only crosslinks above the estimated 1% FDR threshold. Note that the following command will produce the -same output (values >= 1 will automatically divided by 100): +same output (FDR values >= 1 will automatically be divided by 100): ```bash python msannika_fdr.py DSSO_Crosslinks.xlsx -fdr 1 From 959279536c10db9ea14a1993bbbd8a7937076e8b Mon Sep 17 00:00:00 2001 From: Micha Birklbauer Date: Thu, 11 Jan 2024 16:30:48 +0100 Subject: [PATCH 27/27] fixes --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 60864b7..39f23fc 100644 --- a/README.md +++ b/README.md @@ -69,9 +69,9 @@ python msannika_fdr.py DSSO_CSMs.xlsx -fdr 0.01 This will will validate the input CSMs for estimated 1% FDR and will generate a a file `DSSO_CSMs_validated.xlsx` containing only CSMs above the estimated 1% FDR threshold. Furthermore, it will group the input CSMs to crosslinks and -output them to the file `DSSO_CSMs_crosslinks.xlsx` and the validate those +output them to the file `DSSO_CSMs_crosslinks.xlsx` and then validate those crosslinks for 1% estimated FDR and store the result in -`DSSO_CSMs_crosslinks_validated.xlsx` +`DSSO_CSMs_crosslinks_validated.xlsx`. You can also supply several files to the script like this: @@ -80,7 +80,7 @@ python msannika_fdr.py DSSO_CSMs.xlsx DSSO_Crosslinks.xlsx -fdr 0.01 ``` This will process the input files seperately and sequentially and produce the -as mentioned above: +files as mentioned above: - `DSSO_Crosslinks_validated.xlsx` - `DSSO_CSMs_validated.xlsx` - `DSSO_CSMs_crosslinks.xlsx`