From 74d94d7813866d83d4f4bd6d062f165abf7bd547 Mon Sep 17 00:00:00 2001 From: Michael Lazear Date: Wed, 20 Jul 2022 13:33:51 -0700 Subject: [PATCH] Change integration tests to use ms2 files --- README.md | 11 +- figures/TMT_IDs.png | Bin 137399 -> 256935 bytes figures/TMT_Panel.png | Bin 195429 -> 216090 bytes src/bin/carina.rs | 45 +- src/database.rs | 13 +- src/spectrum.rs | 36 +- tests/.gitignore | 5 +- tests/LQSRPAAPPAPGPGQLTLR.json | 1140 -------------------------------- tests/LQSRPAAPPAPGPGQLTLR.ms2 | 291 ++++++++ tests/analyze.py | 32 +- tests/integration.rs | 17 +- tests/q_value.py | 9 + 12 files changed, 364 insertions(+), 1235 deletions(-) delete mode 100644 tests/LQSRPAAPPAPGPGQLTLR.json create mode 100644 tests/LQSRPAAPPAPGPGQLTLR.ms2 create mode 100644 tests/q_value.py diff --git a/README.md b/README.md index ea8798a..ee2e777 100644 --- a/README.md +++ b/README.md @@ -45,15 +45,14 @@ Data repository: [PXD016766](http://proteomecentral.proteomexchange.org/cgi/GetD Performance results: (Intel i7-12700KF + 32GB RAM) -- ~40 seconds to process 12 files, using less than 4GB of RAM -- Active scanning: ~25,000 scans/s (can be tuned to use more ram and go 5x faster!) -- Amortized scanning: ~7,000 scans/s (most time used on fragment indexing, IO) +- ~30 seconds to process 12 files, using less than 4GB of RAM +- Active scanning: ~45,000 scans/s for narrow window (can be tuned to use more ram and go 5x faster!) ### Search methods - MS2 files generated using the [ProteoWizard MSConvert tool](http://www.proteowizard.org/download.html) -- MSFragger and Comet were configured with analogous parameters (50ppm precursor tolerance, 10ppm fragment tolerance - or for Comet setting `fragment_bin_tol` to 0.02 Da). +- MSFragger and Comet were configured with analogous parameters (+/- 25 ppm precursor tolerance, +/- 10 ppm fragment tolerance - or for Comet setting `fragment_bin_tol` to 0.02 Da). - [Mokapot](https://github.com/wfondrie/mokapot) was then used to refine FDR for all search results Carina search settings file: @@ -62,7 +61,7 @@ Carina search settings file: "database": { "bucket_size": 8192, "fragment_min_mz": 75.0, - "fragment_max_mz": 4000.0, + "fragment_max_mz": 2000.0, "peptide_min_len": 5, "peptide_max_len": 50, "decoy": true, @@ -75,7 +74,7 @@ Carina search settings file: "fasta": "UP000005640_9606.fasta" }, "precursor_tol": { - "ppm": 50.0 + "ppm": 25.0 }, "fragment_tol": { "ppm": 10.0 diff --git a/figures/TMT_IDs.png b/figures/TMT_IDs.png index 64ac688acec969c64ecc2ea728d52705c117f054..87d1f4164540ca411d3c9465dfdfa00568695aed 100644 GIT binary patch literal 256935 zcmeFZWmuNk-agEjV<2NIBA^n2pd#HWI&?@k0@5PV4UT~gii*-A-5ruD0wPN1O$n$p zNH_e?m`?^;AerK(9Ur9lddMoW#Dk>^!X{ig!R8%|uqN3W6 z_U9)2$?N8xApA$r;i9I4ijAp*v!R^{mAs+D^{X}xS1pVfolNZPEo`oFpX5DxhJ(@E z!Qr~S(5X|_|N8?cZS2fWvGXxp#D{FTE~RBpMRoER`QINd(c(^2e^60LUpS}g5;D^1 z?4a5-H#eckzTy0~+xrr3On31*{Pm}l%C{58x2|Jne{j#}+{R0PMaAv8v@^>2^x3ls 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- for idx in (0..q_values.len()).rev() { - q_min = q_min.min(q_values[idx]); - q_values[idx] = q_min; - } + // let mut q_values = vec![0.0; scores.len()]; + // let mut decoy = 1; + // let mut target = 0; + + // for (idx, score) in scores.iter().enumerate() { + // match self.db[score.peptide] { + // TargetDecoy::Target(_) => target += 1, + // TargetDecoy::Decoy(_) => decoy += 1, + // } + // q_values[idx] = decoy as f32 / target as f32; + // } + + // // Reverse array, and calculate the cumulative minimum + // let mut q_min = 1.0f32; + // for idx in (0..q_values.len()).rev() { + // q_min = q_min.min(q_values[idx]); + // q_values[idx] = q_min; + // } let mut reporting = Vec::new(); if scores.is_empty() { @@ -182,7 +182,8 @@ impl<'db> Scorer<'db> { matched_peaks: better.matched_b + better.matched_y, summed_intensity: better.summed_b + better.summed_y, total_candidates: scores.len(), - q_value: q_values[idx], + // q_value: q_values[idx], + q_value: 0.0, }) } reporting @@ -265,7 +266,7 @@ fn main() -> Result<(), Box> { let mut pin_paths = Vec::with_capacity(search.ms2_paths.len()); for ms2_path in &search.ms2_paths { - let spectra = read_spectrum(ms2_path)? + let spectra = read_ms2(ms2_path)? .into_iter() .map(|spectra| sp.process(spectra)) .collect::>(); @@ -273,7 +274,7 @@ fn main() -> Result<(), Box> { let start = Instant::now(); let scores: Vec = spectra .par_iter() - // .progress() + .progress() .flat_map(|spectra| scorer.score(spectra)) .collect(); let duration = Instant::now() - start; diff --git a/src/database.rs b/src/database.rs index ef9162b..ae54119 100644 --- a/src/database.rs +++ b/src/database.rs @@ -1,18 +1,13 @@ -use crate::fasta::Trypsin; +use crate::fasta::{Fasta, Trypsin}; +use crate::ion_series::{IonSeries, Kind}; +use crate::mass::Tolerance; use crate::peptide::{Peptide, TargetDecoy}; use crate::spectrum::ProcessedSpectrum; -use crate::{ - fasta::Fasta, - ion_series::{IonSeries, Kind}, - mass::{Tolerance, PROTON}, -}; - use log::error; use rayon::prelude::*; use serde::{Deserialize, Serialize}; -use std::hash::Hash; - use std::collections::{HashMap, HashSet}; +use std::hash::Hash; use std::path::PathBuf; #[derive(Deserialize)] diff --git a/src/spectrum.rs b/src/spectrum.rs index 6c9fa1f..3ddbf3d 100644 --- a/src/spectrum.rs +++ b/src/spectrum.rs @@ -1,7 +1,3 @@ -use std::collections::BTreeMap; - -use serde::Deserialize; - use crate::mass::PROTON; pub struct SpectrumProcessor { @@ -17,8 +13,6 @@ pub struct ProcessedSpectrum { pub charge: u8, pub rt: f32, pub peaks: Vec<(f32, f32)>, - // pub mz: Vec, - // pub int: Vec, } impl SpectrumProcessor { @@ -32,8 +26,6 @@ impl SpectrumProcessor { pub fn process(&self, mut s: Spectrum) -> ProcessedSpectrum { let charge = self.max_fragment_charge.min(s.charge); - // let mut mz = Vec::with_capacity(charge as usize * self.take_top_n); - // let mut int = Vec::with_capacity(charge as usize * self.take_top_n); let mut peaks = Vec::with_capacity(charge as usize * self.take_top_n); s.peaks.sort_by(|(_, a), (_, b)| b.total_cmp(&a)); @@ -45,9 +37,9 @@ impl SpectrumProcessor { // OK, this bit is kinda weird - to save memory, instead of calculating theoretical // m/z's for different charge states, we instead resample the experimental spectra // - // We assume that the m/z we are observing are all at charge state 1, and we - // want to convert them to higher charge states in order to simulate a calculated - // theoretical fragment with this m/z + // We assume that the m/z we are observing are potentially at charge state >1, and we + // want to convert them to charge state = 1 (well, really neutral monoisotopic mass) + // in order to simulate a calculated theoretical fragment with a higher charge let fragment_mz = (fragment_mz - PROTON) * charge as f32; if fragment_mz < self.max_fragment_mz { peaks.push((fragment_mz, fragment_int.sqrt())); @@ -58,39 +50,23 @@ impl SpectrumProcessor { // Sort by m/z peaks.sort_by(|a, b| a.0.total_cmp(&b.0)); - // for (Intensity(fragment_int), fragment_mz) in s.peaks.iter().rev().take(self.take_top_n) { - // for charge in 1..=charge { - // let fragment_mz = (fragment_mz * charge as f32) - (charge as f32 * PROTON); - // if fragment_mz < self.max_fragment_mz { - // mz.push(fragment_mz); - // int.push(fragment_int.sqrt()); - // } - // } - // } - - // dbg!(mz.len()); - ProcessedSpectrum { scan: s.scan, monoisotopic_mass: s.precursor_mass - PROTON, charge: s.charge, rt: s.rt, peaks, - // mz, - // int, } } } /// An observed MS2 spectrum -#[derive(Clone, Default, Debug, Deserialize)] -// #[cfg_attr(test, derive(Deserialize))] +#[derive(Clone, Default, Debug)] pub struct Spectrum { scan: u32, rt: f32, precursor_mass: f32, charge: u8, - // peaks: BTreeMap, peaks: Vec<(f32, f32)>, } @@ -108,7 +84,7 @@ impl std::cmp::Ord for Intensity { } /// Read a `.ms2` file -pub fn read_spectrum>(path: P) -> std::io::Result> { +pub fn read_ms2>(path: P) -> std::io::Result> { let buf = std::fs::read_to_string(path)?; let mut spectra = Vec::new(); let mut current = Spectrum::default(); @@ -141,10 +117,10 @@ pub fn read_spectrum>(path: P) -> std::io::Result()); let mz = ws.next().unwrap().unwrap(); let abundance = ws.next().unwrap().unwrap(); - // current.peaks.insert(Intensity(abundance), mz); current.peaks.push((mz, abundance)); } } + spectra.push(current); Ok(spectra) } diff --git a/tests/.gitignore b/tests/.gitignore index 9596673..7229340 100644 --- a/tests/.gitignore +++ b/tests/.gitignore @@ -1,2 +1,3 @@ -!LQSRPAAPPAPGPGQLTLR.json -pxd/ \ No newline at end of file +pxd/ +fragpipe/ +!LQSRPAAPPAPGPGQLTLR.ms2 \ No newline at end of file diff --git a/tests/LQSRPAAPPAPGPGQLTLR.json b/tests/LQSRPAAPPAPGPGQLTLR.json deleted file mode 100644 index 6b1ae5f..0000000 --- a/tests/LQSRPAAPPAPGPGQLTLR.json +++ /dev/null @@ -1,1140 +0,0 @@ -{ - "scan": 30069, - "rt": 108.28533333333333, - "precursor_mass": 1927.0886370899998, - "charge": 3, - "peaks": [ - [ - 112.08728790283203, - 25014.125 - ], - [ - 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index 0000000..90d21f6 --- /dev/null +++ b/tests/LQSRPAAPPAPGPGQLTLR.ms2 @@ -0,0 +1,291 @@ +H This scan was extracted from the following resource: +H An Ultra-tolerant Database Search Identifies more than 100,000 Modified Peptides +H PXD001468 +H b1906_293T_proteinID_01A_QE3_122212.mzXML +H Chick, JM et al. https://www.ncbi.nlm.nih.gov/pubmed?term=26076430 +S 30069 +Z 3 1927.0886370899998 +I RetTime 108.28533333333333 +112.0873 25014 +115.0874 90977 +120.0815 29301 +126.0556 116604 +127.0867 539149 +128.0902 29451 +131.1180 314760 +141.1022 281695 +147.1137 11771 +155.0815 1250203 +155.1831 12162 +156.0855 89824 +158.0930 98420 +167.1181 128382 +169.0972 481629 +172.1080 27529 +175.1190 675764 +176.1222 25046 +177.7472 14463 +183.1493 132005 +186.0880 21576 +186.1243 27365 +187.1446 16571 +195.1128 446566 +195.1294 31061 +197.0910 24271 +197.1283 27265 +205.2737 17786 +208.0969 44800 +211.1443 100221 +212.1035 102424 +212.1389 282360 +212.9126 14531 +213.1408 23916 +214.1556 39300 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141631 +1116.6345 85550 +1143.6226 443099 +1144.6267 333225 +1145.6390 116556 +1146.6378 27397 +1203.6763 37582 +1204.6929 33510 +1494.1670 25172 \ No newline at end of file diff --git a/tests/analyze.py b/tests/analyze.py index 209df16..f12c98f 100644 --- a/tests/analyze.py +++ b/tests/analyze.py @@ -54,24 +54,22 @@ def __init__(self): ).set_index("scannr") def dump_scan(self, peptide: str, scan): - with open(f'{peptide}.json','w') as f: - rt = scan["retentionTime"] - precursor_mz = scan["precursorMz"][0]["precursorMz"] - precursor_charge = scan["precursorMz"][0]["precursorCharge"] - precursor_mz = ( - (precursor_mz * precursor_charge) - - (precursor_charge * 1.007_276_4) - + 1.007_276_4 - ) - data = { - 'scan': int(scan['num']), - 'rt': float(rt), - 'precursor_mass': precursor_mz, - 'charge': int(precursor_charge), - 'peaks': [(float(x), float(y)) for x,y in zip(scan["m/z array"], scan['intensity array'])], - } + rt = scan["retentionTime"] + precursor_mz = scan["precursorMz"][0]["precursorMz"] + precursor_charge = scan["precursorMz"][0]["precursorCharge"] + precursor_mz = ( + (precursor_mz * precursor_charge) + - (precursor_charge * 1.007_276_4) + + 1.007_276_4 + ) + df = pd.DataFrame(dict(mz=scan['m/z array'], intensity=scan['intensity array'])) + df.loc[:,'precursor_charge'] = precursor_charge + df.loc[:,'precursor_mz'] = precursor_mz + df.loc[:,'scan'] = scan['num'] + df.loc[:,'rt'] = rt + print(df) + df.to_csv(f"{peptide}.csv") - f.write(json.dumps(data, indent=2)) def plot(self, specific_scan: Optional[int]): diff --git a/tests/integration.rs b/tests/integration.rs index aae2173..df85c43 100644 --- a/tests/integration.rs +++ b/tests/integration.rs @@ -3,7 +3,7 @@ use carina::fasta::{Digest, Trypsin}; use carina::ion_series::{IonSeries, Kind}; use carina::mass::Tolerance; use carina::peptide::Peptide; -use carina::spectrum::{Spectrum, SpectrumProcessor}; +use carina::spectrum::SpectrumProcessor; use std::collections::HashMap; const SEQUENCE: &'static str = " @@ -20,11 +20,11 @@ VWPFEKVADAMKQMQEKKNVGKVLLVPGPEKEN"; /// Data from PXD001468 - searched with 10ppm precursor and fragment tolerance /// Top hit after FDR refinement using [mokapot](https://github.com/wfondrie/mokapot) pub fn peptide_id() -> Result<(), Box> { - let data: &str = include_str!("LQSRPAAPPAPGPGQLTLR.json"); - let spectrum: Spectrum = serde_json::from_str(data)?; + let spectrum = carina::spectrum::read_ms2("tests/LQSRPAAPPAPGPGQLTLR.ms2")?; + assert_eq!(spectrum.len(), 1); let sp = SpectrumProcessor::new(100, 2, 1500.0); - let processed = sp.process(spectrum); + let processed = sp.process(spectrum[0].clone()); assert!(processed.peaks.len() <= 300); let sequence = SEQUENCE.split_whitespace().collect::(); @@ -87,12 +87,11 @@ pub fn peptide_id() -> Result<(), Box> { // We use a funky strategy to simulate charge states (see [`SpectrumProcessor`]) // Confirm that we see the right ID's! pub fn confirm_charge_state_simulation() -> Result<(), Box> { - let data: &str = include_str!("LQSRPAAPPAPGPGQLTLR.json"); - let spectrum: Spectrum = serde_json::from_str(data)?; + let spectrum = carina::spectrum::read_ms2("tests/LQSRPAAPPAPGPGQLTLR.ms2")?; + assert_eq!(spectrum.len(), 1); - // charge state = 1, e.g. don't simulate higher states - let sp = SpectrumProcessor::new(100, 1, 1500.0); - let processed = sp.process(spectrum); + let sp = SpectrumProcessor::new(100, 2, 1500.0); + let processed = sp.process(spectrum[0].clone()); assert!(processed.peaks.len() <= 300); let peptide = Peptide::try_from(&Digest { diff --git a/tests/q_value.py b/tests/q_value.py new file mode 100644 index 0000000..543cc7c --- /dev/null +++ b/tests/q_value.py @@ -0,0 +1,9 @@ +import pandas as pd +import matplotlib.pyplot as plt +import seaborn as sns + +df = pd.read_csv('LQSRPAAPPAPGPGQLTLR.ms2.carina.pin', sep='\t') + +sns.displot(data=df, x='hyperscore', hue='label', bins=50, kde=True) +plt.show(block=True) +