12 research outputs found
Proteogenomics Dashboard for the Human Proteome Project
<i>dasHPPboard</i> is a novel proteomics-based dashboard
that collects and reports the experiments produced by the Spanish
Human Proteome Project consortium (SpHPP) and aims to help HPP to
map the entire human proteome. We have followed the strategy of analog
genomics projects like the Encyclopedia of DNA Elements (ENCODE),
which provides a vast amount of data on human cell lines experiments.
The dashboard includes results of shotgun and selected reaction monitoring
proteomics experiments, post-translational modifications information,
as well as proteogenomics studies. We have also processed the transcriptomics
data from the ENCODE and Human Body Map (HBM) projects for the identification
of specific gene expression patterns in different cell lines and tissues,
taking special interest in those genes having little proteomic evidence
available (missing proteins). Peptide databases have been built using
single nucleotide variants and novel junctions derived from RNA-Seq
data that can be used in search engines for sample-specific protein
identifications on the same cell lines or tissues. The <i>dasHPPboard</i> has been designed as a tool that can be used to share and visualize
a combination of proteomic and transcriptomic data, providing at the
same time easy access to resources for proteogenomics analyses. The <i>dasHPPboard</i> can be freely accessed at: http://sphppdashboard.cnb.csic.es
PACOM: A Versatile Tool for Integrating, Filtering, Visualizing, and Comparing Multiple Large Mass Spectrometry Proteomics Data Sets
Mass-spectrometry-based
proteomics has evolved into a high-throughput
technology in which numerous large-scale data sets are generated from
diverse analytical platforms. Furthermore, several scientific journals
and funding agencies have emphasized the storage of proteomics data
in public repositories to facilitate its evaluation, inspection, and
reanalysis. As a consequence, public proteomics
data repositories are growing rapidly. However, tools are needed to
integrate multiple proteomics data sets to compare different experimental
features or to perform quality control analysis. Here, we present
a new Java stand-alone tool, Proteomics Assay COMparator (PACOM),
that is able to import, combine, and simultaneously compare numerous
proteomics experiments to check the integrity of the proteomic data
as well as verify data quality. With PACOM, the user can detect source
of errors that may have been introduced in any step of a proteomics
workflow and that influence the final results. Data sets can be easily
compared and integrated, and data quality and reproducibility can
be visually assessed through a rich set of graphical representations
of proteomics data features as well as a wide variety of data filters.
Its flexibility and easy-to-use interface make PACOM a unique tool
for daily use in a proteomics laboratory. PACOM is available at https://github.com/smdb21/pacom
Enhanced Missing Proteins Detection in NCI60 Cell Lines Using an Integrative Search Engine Approach
The Human Proteome
Project (HPP) aims deciphering the complete
map of the human proteome. In the past few years, significant efforts
of the HPP teams have been dedicated to the experimental detection
of the missing proteins, which lack reliable mass spectrometry evidence
of their existence. In this endeavor, an in depth analysis of shotgun
experiments might represent a valuable resource to select a biological
matrix in design validation experiments. In this work, we used all
the proteomic experiments from the NCI60 cell lines and applied an
integrative approach based on the results obtained from Comet, Mascot,
OMSSA, and X!Tandem. This workflow benefits from the complementarity
of these search engines to increase the proteome coverage. Five missing
proteins C-HPP guidelines compliant were identified, although further
validation is needed. Moreover, 165 missing proteins were detected
with only one unique peptide, and their functional analysis supported
their participation in cellular pathways as was also proposed in other
studies. Finally, we performed a combined analysis of the gene expression
levels and the proteomic identifications from the common cell lines
between the NCI60 and the CCLE project to suggest alternatives for
further validation of missing protein observations
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study