Biology subjects

Perez-Cano, L.

Publications and source records attributed to Perez-Cano, L..

3 recordsLinked to original sources

bioRxiv2025

NGSTroubleFinder: A tool for detection and quantification of contamination and kinship across human NGS data

SummaryQuality control is a fundamental but often neglected step in any NGS pipeline. Detecting issues like cross-sample contamination and sample swaps is essential to control the data integrity. Here, we present NGSTroubleFinder, a novel python tool to detect cross-sample contamination in human Whole-Genome and Whole-Transcriptome Sequencing data, sample swaps and mismatches between the reported and the inferred genetic and transcriptomic sexes. NGSTroubleFinder is implemented in Python and incorporates a custom-built parallelized pileup engine written in C. The tool reports extensive information on the samples both in textual and HTML format including key plots for easy interpretation of the results. Availability and ImplementationNGSTroubleFinder is written in Python and C, and it can be easily installed with pip. The tool source code and the models are freely available on github (https://github.com/STALICLA-RnD/NGSTroubleFinder) and a containerized version is available on dockerhub (https://hub.docker.com/r/staliclarnd/ngstroublefinder).

bioinformatics↗

bioRxiv2020

Network signature of complement component 4 variation in the human brain identifies convergent molecular risk for schizophrenia

The most significant common variant association for schizophrenia (SCZ) reflects increased expression of the complement component 4A (C4A). Yet, it remains unclear how C4A interacts with other SCZ risk genes and whether the complement system is more broadly implicated in SCZ pathogenesis. Here, we integrate several existing, large-scale genetic and transcriptomic datasets to interrogate the functional role of the complement system and C4A in the human brain. Surprisingly, we find no significant genetic enrichment among known complement system genes for SCZ. Conversely, brain co-expression network analyses using C4A as a seed gene revealed that genes down-regulated when C4A expression increased exhibit strong and specific genetic enrichment for SCZ risk. This convergent genomic signal reflected neuronal, synaptic processes and was sexually dimorphic and most prominent in frontal cortical brain regions. Overall, these results indicate that synaptic pathways--rather than the complement system--are the driving force conferring SCZ risk.

genomics↗

bioRxiv2018

Whole genome sequencing in multiplex families reveals novel inherited and de novo genetic risk in autism

Genetic studies of autism spectrum disorder (ASD) have revealed a complex, heterogeneous architecture, in which the contribution of rare inherited variation remains relatively un-explored. We performed whole-genome sequencing (WGS) in 2,308 individuals from families containing multiple affected children, including analysis of single nucleotide variants (SNV) and structural variants (SV). We identified 16 new ASD-risk genes, including many supported by inherited variation, and provide statistical support for 69 genes in total, including previously implicated genes. These risk genes are enriched in pathways involving negative regulation of synaptic transmission and organelle organization. We identify a significant protein-protein interaction (PPI) network seeded by inherited, predicted damaging variants disrupting highly constrained genes, including members of the BAF complex and established ASD risk genes. Analysis of WGS also identified SVs effecting non-coding regulatory regions in developing human brain, implicating NR3C2 and a recurrent 2.5Kb deletion within the promoter of DLG2. These data lend support to studying multiplex families for identifying inherited risk for ASD. We provide these data through the Hartwell Autism Research and Technology Initiative (iHART), an open access cloud-computing repository for ASD genetics research.

genomics↗