A machine-readable specification for genomics assays

Abstract

Understanding the structure of sequenced fragments from genomics libraries is essential for accurate read preprocessing. Currently, different assays and sequencing technologies require custom scripts and programs that do not leverage the common structure of sequence elements present in genomics libraries. We present seqspec, a machine-readable specification for libraries produced by genomics assays that facilitates standardization of preprocessing and enables tracking and comparison of genomics assays. The specification and associated seqspec command line tool is available at https://github.com/IGVF/seqspec.

Universal preprocessing of single-cell genomics data

“…Elements such as barcodes, unique molecular identifiers (UMIs), and genomic features such as cDNA must be accurately identified and appropriately parsed by preprocessing tools to ensure that cataloging, error correcting, and counting are correctly performed. To enable proper element identification and universal preprocessing, we use the seqspec index command (Booeshaghi, Chen, and Pachter 2023) to extract sequenced elements in a tool-specific manner and perform read cataloging against the previously-indexed categories. This indexing strategy correctly identifies and extracts relevant single-cell features in all assay types, a result of the consistent and controlled vocabulary of the seqspec specification.…”

“…The physical-isolation and molecular-capture methods used for an assay are reflected in the structure of reads produced by these methods (Figure 1). The seqspec assay specification (Booeshaghi, Chen, and Pachter 2023) provides a machine-readable format for describing this structure, thereby translating the organizational themes of single-cell genomics into a medium that can, in principle, facilitate automatic and universal preprocessing of single-cell genomics data. While several tools have been developed for preprocessing data from different single-cell RNA-seq assays (He et al 2022; Battenberg et al 2022; Melsted et al 2021), we demonstrate that seqspec (Booeshaghi, Chen, and Pachter 2023), along with kallisto bustools (Melsted et al 2021), kITE (Sina Booeshaghi et al 2022) and snATAK (Sina Booeshaghi, Gao, and Pachter 2023), can in principle be used for preprocessing data from any single-cell genomics assay.…”

Reciprocal crosstalk between Th17 and mesothelial cells promotes metastasis‐associated adhesion of ovarian cancer cells

“…The reference consisted of the Homo Sapiens genome sequence GRCH38.p13 retrieved together with the used gene models from Ensembl 108, extended with the Rhapsody sample tags for Homo sapiens. Cell barcodes were retrieved from 45,46 …”

“…Cell barcodes were retrieved from. 45,46 The targeted gene set consisted of the Becton Dickinson Rhapsody Onco-BC Targeted Panel (https://scomix.bd. com/hc/article_attachments/13766899704717) and a specifically selected panel to detect TNF+IL-17A regulated genes in mesothelial cells based on our data described below in the Results section.…”

simpleaf: A simple, flexible, and scalable framework for single-cell transcriptomics data processing using alevin-fry

“…To date, the community has put significant efforts into documenting and categorizing the library layout for many existing sequencing assays [19, 10, 20] and developing general parsers for such protocols [21, 22, 10, 23]. Of course, these tools, or their relevant components could also be applied to this task, with the user handling the appropriate bookkeeping.…”