Marc Salit

This paper develops Ribo-ITP to measure ribosome occupancy in single cells during early mouse development, revealing differential translation efficiency and allele-specific ribosome engagement.

This paper expands genome benchmarking to include difficult-to-map regions using linked and long reads, identifying more false negatives in variant calling.

The paper evaluates the detection of technically challenging variants in NGS workflows using synthetic specimens and clinical data from 450,000 patients, finding significant variability in detection rates.

The paper develops a diploid assembly-based benchmark for variants in the MHC region using HG002 data, identifying 21496 small variants with high concordance to clinical HLA types.

The paper introduces SVCurator, a crowdsourcing app for evaluating structural variants in the human genome, finding high concordance among curators and with existing benchmarks.

The paper assembles and annotates a population-specific Ashkenazi human reference genome, showing improved contiguity and completeness compared to GRCh38.

Genome in a Bottle benchmark of 12745 sequence-resolved insertions and deletions of 50 bp or more, integrating 19 calling methods, scores false negatives and false positives alike.

The paper presents high-coverage long-read sequencing data from a Han Chinese trio for developing and evaluating long-read bioinformatics methods.

The paper develops a reproducible pipeline to integrate sequencing datasets for high-confidence SNP, indel, and reference calls in five human genomes, showing improved variant detection compared to prior methods.

The paper develops standardized tools and best practices for benchmarking germline small variant calls in human genomes using truth sets and performance metrics.

The paper examines the need for orthogonal confirmation of NGS-detected variants in clinical testing and develops criteria to identify false positives with high accuracy.

The paper identifies key experimental factors affecting growth and productivity of engineered E. coli strains and proposes a Minimum Information Standard for Engineered Organism Experiments.

The paper introduces CrowdVariant, a crowdsourcing framework to classify copy number variants (CNVs) using NGS data, and identifies 1,781 high-confidence CNVs in a reference sample.

The paper evaluates 16S rRNA marker gene analysis pipelines using a mixture dataset of human stool samples, finding DADA2 better captures specific features than Mothur and QIIME.

The paper introduces genomeview, a Python-based genomics visualization engine designed for extensibility and integration into analysis pipelines.

The paper evaluates reference samples for genome-scale miRNA profiling and develops metrics and an online pipeline to assess measurement performance.

This study evaluates synthetic specimens with challenging variants across 10 NGS workflows, finding limited variant detection consistency and highlighting bioinformatic limitations.

The paper quantifies translation initiation in E. coli from all 64 codons, finding that 46 codons can initiate translation at levels up to 2% relative to AUG.

This paper introduces GROC-SVs, a method for detecting and assembling structural variants using read cloud data, showing improved specificity and enabling complex breakpoint reconstruction in cancer samples.

The paper evaluates ERCC RNA controls using a modified Latin square design across multiple platforms to assess their performance in quantifying RNA transcripts.

The paper shows that red fluorescent proteins can bias cell density measurements by increasing optical density at 600 nm, suggesting measuring at 700 nm avoids this issue.

The paper evaluates using RNA-seq mixtures as process controls to benchmark measurement performance and assess bias and variability.

svviz validates structural variants by visualizing relevant reads aligned to candidate SV alleles, enabling evidence assessment and breakpoint refinement.