【2】蛋白鉴定软件之Comet

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所属分类:生物信息学

目录
官网:
1993年开发,持续更新,免费开源
适用Windows/Linux
多线程,支持多种输入输出格式:输入谱图文件(mzXML, mzML, mgf, or ms2/cms2),输出.pep.xml/.pin.xml/.sqt/.out等文件
运行:
comet.exe input.mzXML
comet.exe input.mzML
comet.exe input.mgf
comet.exe input.ms2
comet.exe *.ms2 #支持多文件输入

其他整合了Comet的工具:

2.下载安装
下载UI界面版本:.,用户指南:
下载Linux版本:
依然只试用Linux版本。
unzip comet_2019015.zip

3.软件使用
运行非常简单,软件后调用参数配置文件和谱图原始文件即可。
参数配置文件在官网解释得非常详细:。同时针对不同质谱仪的一级和二级质量误差,官方提供了3个示例参数文件:
●  用于低一级和二级误差,如 ion trap
●  用于高一级误差和低二级误差,如Velos-Orbitrap
●  用于高一级和二级误差,如 Q Exactive 或 Q-Tof
以高分辨质谱仪为例,以下参数除了数据库设置,大部分参数默认即可:
# comet_version 2019.01 rev. 0
# Comet MS/MS search engine parameters file.
# Everything following the '#' symbol is treated as a comment.
database_name = /some/path/db.fasta
decoy_search = 0 # 0=no (default), 1=concatenated search, 2=separate search
peff_format = 0 # 0=no (normal fasta, default), 1=PEFF PSI-MOD, 2=PEFF Unimod
peff_obo = # path to PSI Mod or Unimod OBO file
num_threads = 0 # 0=poll CPU to set num threads; else specify num threads directly (max 128)
# masses
peptide_mass_tolerance = 20.00
peptide_mass_units = 2 # 0=amu, 1=mmu, 2=ppm
mass_type_parent = 1 # 0=average masses, 1=monoisotopic masses
mass_type_fragment = 1 # 0=average masses, 1=monoisotopic masses
precursor_tolerance_type = 1 # 0=MH+ (default), 1=precursor m/z; only valid for amu/mmu tolerances
isotope_error = 3 # 0=off, 1=0/1 (C13 error), 2=0/1/2, 3=0/1/2/3, 4=-8/-4/0/4/8 (for +4/+8 labeling)
# search enzyme
search_enzyme_number = 1 # choose from list at end of this params file
search_enzyme2_number = 0 # second enzyme; set to 0 if no second enzyme
num_enzyme_termini = 2 # 1 (semi-digested), 2 (fully digested, default), 8 C-term unspecific , 9 N-term unspecific
allowed_missed_cleavage = 2 # maximum value is 5; for enzyme search
# Up to 9 variable modifications are supported
# format: mass residues 0=variable/else binary max_mods_per_peptide term_distance n/c-term required neutral_loss
# e.g. 79.966331 STY 0 3 -1 0 0 97.976896
variable_mod01 = 15.9949 M 0 3 -1 0 0 0.0
variable_mod02 = 0.0 X 0 3 -1 0 0 0.0
variable_mod03 = 0.0 X 0 3 -1 0 0 0.0
variable_mod04 = 0.0 X 0 3 -1 0 0 0.0
variable_mod05 = 0.0 X 0 3 -1 0 0 0.0
variable_mod06 = 0.0 X 0 3 -1 0 0 0.0
variable_mod07 = 0.0 X 0 3 -1 0 0 0.0
variable_mod08 = 0.0 X 0 3 -1 0 0 0.0
variable_mod09 = 0.0 X 0 3 -1 0 0 0.0
max_variable_mods_in_peptide = 5
require_variable_mod = 0
# fragment ions
# ion trap ms/ms: 1.0005 tolerance, 0.4 offset (mono masses), theoretical_fragment_ions = 1
# high res ms/ms: 0.02 tolerance, 0.0 offset (mono masses), theoretical_fragment_ions = 0, spectrum_batch_size = 10000
fragment_bin_tol = 0.02 # binning to use on fragment ions
fragment_bin_offset = 0.0 # offset position to start the binning (0.0 to 1.0)
theoretical_fragment_ions = 0 # 0=use flanking peaks, 1=M peak only
use_A_ions = 0
use_B_ions = 1
use_C_ions = 0
use_X_ions = 0
use_Y_ions = 1
use_Z_ions = 0
use_NL_ions = 0 # 0=no, 1=yes to consider NH3/H2O neutral loss peaks
# output
output_sqtstream = 0 # 0=no, 1=yes write sqt to standard output
output_sqtfile = 0 # 0=no, 1=yes write sqt file
output_txtfile = 0 # 0=no, 1=yes write tab-delimited txt file
output_pepxmlfile = 1 # 0=no, 1=yes write pep.xml file
output_percolatorfile = 0 # 0=no, 1=yes write Percolator tab-delimited input file
print_expect_score = 1 # 0=no, 1=yes to replace Sp with expect in out sqt
num_output_lines = 5 # num peptide results to show
show_fragment_ions = 0 # 0=no, 1=yes for out files only
sample_enzyme_number = 1 # Sample enzyme which is possibly different than the one applied to the search.
# Used to calculate NTT NMC in pepXML output (default=1 for trypsin).
# mzXML parameters
scan_range = 0 0 # start and end scan range to search; either entry can be set independently
precursor_charge = 0 0 # precursor charge range to analyze; does not override any existing charge; 0 as 1st entry ignores parameter
override_charge = 0 # 0=no, 1=override precursor charge states, 2=ignore precursor charges outside precursor_charge range, 3=see online
ms_level = 2 # MS level to analyze, valid are levels 2 (default) or 3
activation_method = ALL # activation method; used if activation method set; allowed ALL, CID, ECD, ETD, ETD+SA, PQD, HCD, IRMPD
# misc parameters
digest_mass_range = 600.0 5000.0 # MH+ peptide mass range to analyze
peptide_length_range = 5 63 # minimum and maximum peptide length to analyze (default 1 63; max length 63)
num_results = 100 # number of search hits to store internally
max_duplicate_proteins = 20 # maximum number of protein names to report for each peptide identification; -1 reports all duplicates
skip_researching = 1 # for '.out' file output only, 0=search everything again (default), 1=don't search if .out exists
max_fragment_charge = 3 # set maximum fragment charge state to analyze (allowed max 5)
max_precursor_charge = 6 # set maximum precursor charge state to analyze (allowed max 9)
nucleotide_reading_frame = 0 # 0=proteinDB, 1-6, 7=forward three, 8=reverse three, 9=all six
clip_nterm_methionine = 0 # 0=leave sequences as-is; 1=also consider sequence w/o N-term methionine
spectrum_batch_size = 15000 # max. # of spectra to search at a time; 0 to search the entire scan range in one loop
decoy_prefix = DECOY_ # decoy entries are denoted by this string which is pre-pended to each protein accession
equal_I_and_L = 1 # 0=treat I and L as different; 1=treat I and L as same
output_suffix = # add a suffix to output base names i.e. suffix "-C" generates base-C.pep.xml from base.mzXML input
mass_offsets = # one or more mass offsets to search (values substracted from deconvoluted precursor mass)
precursor_NL_ions = # one or more precursor neutral loss masses, will be added to xcorr analysis
# spectral processing
minimum_peaks = 10 # required minimum number of peaks in spectrum to search (default 10)
minimum_intensity = 0 # minimum intensity value to read in
remove_precursor_peak = 0 # 0=no, 1=yes, 2=all charge reduced precursor peaks (for ETD), 3=phosphate neutral loss peaks
remove_precursor_tolerance = 1.5 # +- Da tolerance for precursor removal
clear_mz_range = 0.0 0.0 # for iTRAQ/TMT type data; will clear out all peaks in the specified m/z range
# additional modifications
add_Cterm_peptide = 0.0
add_Nterm_peptide = 0.0
add_Cterm_protein = 0.0
add_Nterm_protein = 0.0
add_G_glycine = 0.0000 # added to G - avg. 57.0513, mono. 57.02146
add_A_alanine = 0.0000 # added to A - avg. 71.0779, mono. 71.03711
add_S_serine = 0.0000 # added to S - avg. 87.0773, mono. 87.03203
add_P_proline = 0.0000 # added to P - avg. 97.1152, mono. 97.05276
add_V_valine = 0.0000 # added to V - avg. 99.1311, mono. 99.06841
add_T_threonine = 0.0000 # added to T - avg. 101.1038, mono. 101.04768
add_C_cysteine = 57.021464 # added to C - avg. 103.1429, mono. 103.00918
add_L_leucine = 0.0000 # added to L - avg. 113.1576, mono. 113.08406
add_I_isoleucine = 0.0000 # added to I - avg. 113.1576, mono. 113.08406
add_N_asparagine = 0.0000 # added to N - avg. 114.1026, mono. 114.04293
add_D_aspartic_acid = 0.0000 # added to D - avg. 115.0874, mono. 115.02694
add_Q_glutamine = 0.0000 # added to Q - avg. 128.1292, mono. 128.05858
add_K_lysine = 0.0000 # added to K - avg. 128.1723, mono. 128.09496
add_E_glutamic_acid = 0.0000 # added to E - avg. 129.1140, mono. 129.04259
add_M_methionine = 0.0000 # added to M - avg. 131.1961, mono. 131.04048
add_O_ornithine = 0.0000 # added to O - avg. 132.1610, mono 132.08988
add_H_histidine = 0.0000 # added to H - avg. 137.1393, mono. 137.05891
add_F_phenylalanine = 0.0000 # added to F - avg. 147.1739, mono. 147.06841
add_U_selenocysteine = 0.0000 # added to U - avg. 150.0379, mono. 150.95363
add_R_arginine = 0.0000 # added to R - avg. 156.1857, mono. 156.10111
add_Y_tyrosine = 0.0000 # added to Y - avg. 163.0633, mono. 163.06333
add_W_tryptophan = 0.0000 # added to W - avg. 186.0793, mono. 186.07931
add_B_user_amino_acid = 0.0000 # added to B - avg. 0.0000, mono. 0.00000
add_J_user_amino_acid = 0.0000 # added to J - avg. 0.0000, mono. 0.00000
add_X_user_amino_acid = 0.0000 # added to X - avg. 0.0000, mono. 0.00000
add_Z_user_amino_acid = 0.0000 # added to Z - avg. 0.0000, mono. 0.00000
# COMET_ENZYME_INFO _must_ be at the end of this parameters file
[COMET_ENZYME_INFO]
0. No_enzyme 0 - -
1. Trypsin 1 KR P
2. Trypsin/P 1 KR -
3. Lys_C 1 K P
4. Lys_N 0 K -
5. Arg_C 1 R P
6. Asp_N 0 D -
7. CNBr 1 M -
8. Glu_C 1 DE P
9. PepsinA 1 FL P
10. Chymotrypsin 1 FWYL P

一般设置数据库database_name,线程数num_threads,特异性酶search_enzyme_number = 1。(如果是多肽组学,设置为非特异性酶search_enzyme_number = 0)
运行命令:
comet.2019015.linux.exe -P./comet.params.high-high test_1.mzML

谱图文件支持mzXML, mzML, mgf, or ms2/cms2等多种格式,obitrap的高分辨质谱仪(.raw)需要转化。关于Linux上质谱原始数据的格式转化,可参考博文:(-f参数设为1即可得到mzML格式)。
运行结果会出现`test_1.pep.xml,test_1.pin,test_1.txt等文件。主要看txt文件,即为鉴定结果:
第一行:
CometVersion 2019.01 rev. 5 test_1 07/28/2020, 02:12:23 PM /path/to/database/test.fasta

结果表头:
1 scan
2 num
3 charge
4 exp_neutral_mass
5 calc_neutral_mass
6 e-value
7 xcorr
8 delta_cn
9 sp_score
10 ions_matched
11 ions_total
12 plain_peptide
13 modified_peptide
14 prev_aa
15 next_aa
16 protein
17 protein_count
18 modifications

一般也要根据需要,进行后处理。
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