MetaMap, an interactive webtool for the exploration of metatranscriptomic reads in human disease-related RNA-seq data

Abstract

Motivation:The MetaMap resource contains metatranscriptomic expression data from 15 screening >17,000 RNA-seq samples from >400 archived human disease-related studies for viral and microbial reads, so-called "metafeatures". However, navigating this set of large and heterogeneous data is challenging, especially for researchers without bioinformatic expertise.Therefore, a user-friendly interface is needed that allows users to visualize and statistically analyse the data. 20 Results:We developed an interactive frontend to facilitate the exploration of the MetaMap resource. The webtool allows users to query the resource by searching study abstracts for keywords or browsing expression patterns for specific metafeatures. Moreover, users can manually define sample groupings or use the existing annotation for downstream analysis.The web tool provides a large variety of analyses and visualizations including dimension 25 reduction, differential abundance analysis and Krona visualizations. The MetaMap webtool represents a valuable resource for hypothesis generation regarding the impact of the microbiome in human disease. Availability:The presented web tool can be accessed at https://github.com/theislab/MetaMap 30

Metadata retrieval from sequence databases with ffq

“…The extraordinary large volume of user-generated sequencing data available in public databases is increasingly being utilized in research projects alongside novel experiments (Simon et al, 2018;Razmara et al, 2019;Lung et al, 2020;Rajesh et al, 2021;Hippen and Greene, 2021;Wartmann et al, 2021;Kasmanas et al, 2021;Huang et al, 2021;Klie et al, 2021;Booeshaghi et al, 2022). Collation of metadata is crucial for such reuse of publicly available data since it can provide information about the samples assayed and can facilitate the acquisition of raw data.…”

Metadata retrieval from sequence databases with ffq

“…The extraordinary large volume of user-generated sequencing data available in public databases is increasingly being utilized in research projects alongside novel experiments (Simon et al ., 2018; Razmara et al ., 2019; Lung et al ., 2020; Rajesh et al ., 2021; Hippen and Greene, 2021; Wartmann et al ., 2021; Kasmanas et al ., 2021; Huang et al ., 2021; Klie et al ., 2021; Booeshaghi et al ., 2022). Collation of metadata is crucial for such reuse of publicly available data since it can provide information about the samples assayed and can facilitate the acquisition of raw data.…”