Protein Inference Using PIA Workflows and PSI Standard File Formats

Proteomics using
LC–MS/MS has become one of the main methods
to analyze the proteins in biological samples in high-throughput.
But the existing mass-spectrometry instruments are still limited with
respect to resolution and measurable mass ranges, which is one of
the main reasons why shotgun proteomics is the major approach. Here
proteins are digested, which leads to the identification and quantification
of peptides instead. While often neglected, the important step of
protein inference needs to be conducted to infer from the identified
peptides to the actual proteins in the original sample. In this work,
we highlight some of the previously published and newly added features
of the tool PIA – Protein Inference Algorithms, which helps
the user with the protein inference of measured samples. We also highlight
the importance of the usage of PSI standard file formats, as PIA is
the only current software supporting all available standards used
for spectrum identification and protein inference. Additionally, we
briefly describe the benefits of working with workflow environments
for proteomics analyses and show the new features of the PIA nodes
for the KNIME Analytics Platform. Finally, we benchmark PIA against
a recently published data set for isoform detection. PIA is open source
and available for download on GitHub (https://github.com/mpc-bioinformatics/pia) or directly via the community extensions inside the KNIME analytics
platform.