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Start_Here

Brief descriptions and links to my repositories and other content.

  • Start_Here - This repository. Updated January 20, 2024.

Latest Content:

  • mouse_lens_development_Khan2018_reanalysis - A thorough and detailed re-analysis of a TMT-labeled bottom-up quantitative proteomcis study. The experiment is tracking the developing mouse lens proteome at two embryonic ages (E15 and E18, in days) and postnatal ages (P0, P3, P6, and P9). The salient points are:

    • doing quantitative proteomics without using ratios
    • combining multi-plex TMT experiments
    • understanding samples with a few highly abundant proteins
    • understanding how data normalization and statistical testing results are coupled
    • preparing results in ways that facilitate data exploration and discovery

  • PXD030990_human-tear_re-analysis - A re-analysis of human tear samples characterized in a single-shot experimental design. Tear has a few highly abundant proteins that makes deep proteome profiling without fractionation impossible. Single-shot experimental designs have gained popularity but they are much more limiting than seems to be realized. Proteomic depth is a case of getting out what you put in. A single LC run won't get you much. Short gradient single LC runs will get you even less.

  • Human_rhesus_TMT - Analysis discussion of a multi-sample, multi-fraction, multi-kit, multi-species TMTpro experiment. Details how to analyze a 21 rhesus samples, 24 human samples, 45 samples total, 17 channels per plex (15 plus 2 pooled standards) in 3 plexes labeled with TMTpro 18-plex reagents experiment.

  • quantitative_proteomics_data_cleaning - A discussion of basic data cleaning concepts for quantitative proteomics data and some useful notebook quality control (QC) metrics.

Table of Contents:

Blogs

Website Blogs

README Blogs

GitHub markdown (and the auto rendering of repository README.md files as nice webpages) creates a fast way to do technical blogging. Supporting files and images are easier to add to a repository than to a formal website. Repositories can also be great for sharing presentations (meeting content or training resources).

  • talk_to_repo_example - Tutorial on turning talks and posters into GitHub content. (Nov. 2019)
  • Installing R kernel in Jupyter notebooks - How to add an R kernel to Jupyter notebooks. (Aug. 2021)
  • Gene-set-enrichment_STRING-DB - Short tutorial on doing gene set enrichment with STRING-DB. (Sep. 2021)
  • PRIDE_submission_tutorial - A guide to submitting PAW pipeline results to PRIDE. (May 2020)
  • precursor_mass_corrections - Is monoisotopic peak picking for MS2 scans a problem that needs solving? (April 2021)
  • score_distributions_FDR - Get your annoying tail out of my good scores! (April 2021)
  • IRS_validation - Notebooks demonstrating how Internal Reference Scaling (IRS) in multiplex TMT experiments works. (Jan. 2019)
  • human_tear_references - A summary of quantitative tear proteomics references up to April 2022. Stimulated tearing confounds (probably) all these studies. (April 2022)
  • TMT_PAW_pipeline - Details about how TMT labeling is handled in the PAW pipeline. (Oct. 2022)
  • TMT_channel_cross_talk - A deeper dive on adjacent channel cross talk for TMTpro 18-plex. How large is the effect and some pros and cons of correction. (Dec. 2022)
  • Human-plasma_DIA-vs-TMT - An apples-to-aardvarks comparison of human plasma proteomes from DIA versus TMT. (Feb. 2023)
  • PXD011691_reanalysis - Reanalysis of data from PXD011691 - another DIA versus TMT experiment. (Feb. 2023)
  • quantitative_proteomics_data_cleaning - A discussion of basic data cleaning concepts for quantitative proteomics data and some useful notebook quality control (QC) metrics. (April 2023)
  • Human_rhesus_TMT - Analysis discussion of a multi-sample, multi-fraction, multi-kit, multi-species TMTpro experiment. Details how to analyze a 21 rhesus samples, 24 human samples, 45 samples total, 17 channels per plex (15 plus 2 pooled standards) in 3 plexes labeled with TMTpro 18-plex reagents experiment. (Oct. 2023)
  • PXD030990_human-tear_re-analysis - A re-analysis of human tear samples characterized in a single-shot experimental design. Tear has a few highly abundant proteins that makes deep proteome profiling without fractionation impossible. Single-shot experimental designs have gained popularity but they are much more limiting than seems to be realized. Proteomic depth is a case of getting out what you put in. A single LC run won't get you much. Short gradient single LC runs will get you even less. (Nov. 2023)
  • mouse_lens_development_Khan2018_reanalysis - A thorough and detailed re-analysis of a TMT-labeled bottom-up quantitative proteomcis study. The experiment is tracking the developing mouse lens proteome at two embryonic ages (E15 and E18, in days) and postnatal ages (P0, P3, P6, and P9). The salient points are:
    • doing quantitative proteomics without using ratios
    • combining multi-plex TMT experiments
    • understanding samples with a few highly abundant proteins
    • understanding how data normalization and statistical testing results are coupled
    • preparing results in ways that facilitate data exploration and discovery
      (Jan. 2024)

Software

  • PAW_pipeline - The PAW/Comet proteomics pipeline

  • fasta_utilities - Utilities for downloading and prepping FASTA files

  • utilities - Some miscellaneous utility scripts

  • annotations - Scripts for adding UniProt annotations to results lists

  • PAW_BLAST - Scripts for BLAST ortholog matching

  • Z-score_GUI - Script for sliding-window Z-score analyses

Analyses

Internal_Reference_Scaling

Real_Time_Search

PAW_TMT

Other_TMT

MS2_TMT

Spectral_Counting

Meetings

Other_Repositories

Forked Repositories