Time filter

Source Type

Seattle, WA, United States

Keller A.,Rosetta Biosoftware
Methods in molecular biology (Clifton, N.J.)

The LC-MS/MS shotgun proteomics workflow is widely used to identify and quantify sample peptides and proteins. The technique, however, presents a number of challenges for large-scale use, including the diverse raw data file formats output by mass spectrometers, the large false positive rate among peptide assignments to MS/MS spectra, and the loss of connectivity between identified peptides and the sample proteins that gave rise to them. Here we describe the Trans-Proteomic Pipeline, a freely available open source software suite that provides uniform analysis of LC-MS/MS data from raw data to quantified sample proteins. In a straightforward manner, users can extract MS/MS information from raw data of many instrument formats, submit them to search engines for peptide identification, validate the results to remove false hits, combine together results of multiple search engines, infer sample proteins that gave rise to the identified peptides, and perform quantitation at the peptide and protein levels. Source

Rosetta Biosoftware | Entity website

1 100%

Rosetta Biosoftware | Entity website

100200 100

Rosetta Biosoftware | Entity website

1310 1

Zhang L.,Genomics Group | Yin S.,Genomics Group | Miclaus K.,SAS Institute | Chierici M.,Fondazione Bruno Kessler | And 6 more authors.
Pharmacogenomics Journal

The robustness of genome-wide association study (GWAS) results depends on the genotyping algorithms used to establish the association. This paper initiated the assessment of the impact of the Corrected Robust Linear Model with Maximum Likelihood Classification (CRLMM) genotyping quality on identifying real significant genes in a GWAS with large sample sizes. With microarray image data from the Wellcome Trust Case-Control Consortium (WTCCC), 1991 individuals with coronary artery disease (CAD) and 1500 controls, genetic associations were evaluated under various batch sizes and compositions. Experimental designs included different batch sizes of 250, 350, 500, 2000 samples with different distributions of cases and controls in each batch with either randomized or simply combined (4:3 case-control ratios) or separate case-control samples as well as whole 3491 samples. The separate composition could create 2-3% discordance in the single nucleotide polymorphism (SNP) results for quality control/statistical analysis and might contribute to the lack of reproducibility between GWAS. CRLMM shows high genotyping accuracy and stability to batch effects. According to the genotypic and allelic tests (P5.0 × 10 -7), nine significant signals on chromosome 9 were found consistently in all batch sizes with combined design. Our findings are critical to optimize the reproducibility of GWAS and confirm the genetic role in the pathophysiology of CAD. © 2010 Macmillan Publishers Limited. All rights reserved. Source

Discover hidden collaborations