Perform two-pass search to analyze novel peptides and PTMs

FragPipe can be downloaded here. Follow the instructions on that same Releases page to launch the program. See here for help configuring FragPipe.

FragPipe has the ability to perform the “two-pass search” to detect novel peptides and PTMs semi-automatically. It performs the following three steps.

  1. Perform the first search to identify the canonical peptides and/or common PTMs
  2. Generate new “sub mzML” files by excluding the scans having good matches
  3. Perform the second search to identify the novel peptides and/or PTMs
  1. The spectra are not mass calibrated or the mass calibration does not work well
  2. The rescoring tools, such as Percolator, cannot learn a good model in the second search

To address these issues, FragPipe

  1. performs mass calibration in the first search, and then generates sub mzML files using the calibrated spectra
  2. writes the Percolator models (*_percolator.weights files) to the result directory after the first search. These models will be used in the second search.
An alternaive approach to analyze novel/variant peptides

FragPipe can also perform group FDR estimation for the peptides with different levels of evidences. Please check Perform group FDR estimation for different identification groups for details.

Perform two-pass search for the label-free quantification data

  1. Load the LFQ-MBR workflow in the Workflow tab
  2. Load the LC-MS files, assign experiments and bioreplicates (if applicable), and set the Data type to DDA
  3. Load your FASTA file in the Database tab
  4. Go to the Run tab, specify the output directory
  5. [Critical] In the Run tab, enable the Write sub mzML. FragPipe will generate “sub mzML” files containing the scans do not pass the FDR filtering and have the probability smaller than or equal to the Min probability threshold of excluding scans from sub mzML files.

  1. Click run. FragPipe will perform the “first-pass search”.
  2. After FragPipe finish, go back to the Workflow tab
  3. Select the Custom workflow and click Load workflow

  1. Locate the fragpipe-second-pass.workflow file in the result directory and load it
  2. Click Clear files to remove all LC-MS files used in the first-pass search
  3. Click Load manifest, locate the fragpipe-second-pass.manifest file in the result directory, and load it

  1. Go to the Database tab to specify the FASTA file for the second search.
  2. Go to Run tab, specify the new output directory and click Run

Perform two-pass search for the isobaric-labeling data

  1. Load one of the TMT workflow in the Workflow tab
  2. Load the LC-MS files, assign experiments and bioreplicates (if applicable), and set the Data type to DDA
  3. Load your FASTA file in the Database tab
  4. Go to the Quant (Isobaric) tab, configure the sample/channel annotations. Details can be found in the other tutorial
  5. Go to the Run tab, specify the output directory
  6. [Critical] In the Run tab, enable the Write sub mzML. FragPipe will generate “sub mzML” files containing the scans do not pass the FDR filtering and have the probability smaller than or equal to the Min probability threshold of excluding scans from sub mzML files.

  1. Click run. FragPipe will perform the “first-pass search”.
  2. After FragPipe finish, go back to the Workflow tab
  3. Select the Custom workflow and click Load workflow

  1. Locate the fragpipe-second-pass.workflow file in the result directory and load it
  2. Click Clear files to remove all LC-MS files used in the first-pass search
  3. Click Load manifest, locate the fragpipe-second-pass.manifest file in the result directory, and load it

  1. Go to the Database tab to specify the FASTA file for the second search.
  2. Go to the Quant (Isobaric) tab to ensure that the sample/channel annotation is correct.
  3. Go to Run tab, specify the new output directory and click Run



Key References

Desai H, Ofori S, Boatner L, Yu F, Villanueva M, Ung N, Nesvizhskii AI, Backus K. Multi-omic stratification of the missense variant cysteinome, bioRxiv (2023).



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