Name: Phillip Wilmarth
Type: User
Company: Oregon Health & Science University
Bio: Data analyst at OHSU proteomics core since 2003. My nuclear chemistry Ph.D. was from Glenn Seaborg's group, UC Berkeley (1988). Mastodon: @[email protected]
Twitter: pwilmarth
Location: Portland, OR USA
Blog: https://pwilmart.github.io/
Phillip Wilmarth's Projects
Content for ARBF 2020 meeting talk
A spectral counting analysis of the ABRF iPRG 2015 study
GUI tool to add rich annotations to PAW summary files from Swiss-Prot flat text files.
An unbiased comparison of peptide identification performance between SEQUEST, Mascot, and X!Tandem (circa 2013).
IRS normalization poster presented at 2018 San Diego ASMS meeting (Thursday #389) .
Re-analysis of data from childhood acute lymphoblastic leukemia study in Nat. Comm. April 2019
2013 Cascadia Proteomics Symposium talk about extended parsimony protein grouping.
Using Jupyter notebooks in proteomics data analyses talk slides from the 2018 Cascadia Proteomics Symposium
Benchmarking proteomics analyses on desktop computers and in the cloud.
Tandem Mass Tag (TMT) dilution series analysis
Utilities for downloading and managing protein FASTA files.
An apples-to-aardvarks comparison of human plasma proteomes from DIA and TMT
Analysis discussion of a multi-sample, multi-fraction, multi-kit, multi-species TMTpro experiment
Review of 80 or so human tear quantitative proteomics studies
An exploration of internal reference scaling (IRS) normalization in isobaric tagging proteomics experiments.
Analysis of technical replicate channels to more fully validate the internal reference scaling (IRS) method.
Public TMT data comparing MS2 to MS3 methods
Compares PAW and MQ for a 7-channel TMT experiment; compares edgeR to two-sample t-test
Re-analysis of metaplastic breast cancer 27-sample TMT data from the PXD014414 archive.
Re-analysis of Khan 2018 developing mouse lens TMT study (PXD006381)
Developing mouse lens done with MQ
A utility for blasting one protein FASTA file against another FASTA file to find orthologs.
Phospho peptide software for processing Proteome Discoverer PSM export files.
A Comet-based, best practices proteomics pipeline.
Data from Plubell et al., 2017 processed with the PAW pipeline.
Explores precursor mass correction algorithm assumptions and claims
An exploration of how best practices for bottom-up, data-dependent acquisition proteomics are ignored