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Release Notes

The release notes describe what lines were released with each assay, any possible updates on cell lines, data or software, and findings that might help users interpret the data. The release notes might also include bugs that might be fixed since last release, or known issues and workarounds.

70+ projects started using Answer ALS data

1000+ participant clinical, genomic, transcription, and protein expression data types collected

100% data generated by Answer ALS is being made available to the global research community

Release 3.0 (October 2020)

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We have released an additional set of Whole-Genome Sequencing (WGS) data, levels 2-3 (CRAM and VCF), for 475 Participants.
This brings the total number of participants with WGS data to 866!

NOTE: Level 1 data for WGS (raw FASTQs) have been moved from general access and are available by special request.
Please contact us if you require this data.

Data Replacement: WGS ExpansionHunter VCFs (files ending in "eh.vcf") have been re-run and standardized using Illumina's Version 2.5.5 software.

The Analyze tab of our portal has been reintroduced.
Heatmap visualizations for Transcriptomics samples are currently available.

The data portal has a new landing page and release notes tab.

Release 2.1 (April 2020)

Download Package

We have added the following Transcriptomics data:

  • 86 Indexed BAM files
  • 86 Counts files

Release 2.0 (March 2020)

Download Package

We have now released 391 WGS Samples, 85 Epigenomics samples (FASTQ, BAM, Peaks), and 86 Transcriptomics samples (FASTQ, BAM).

Full release metadata package:

  • We’ve added complete Clinical metadata, Participant/Inventory metadata and Portal metadata.
  • All metadata tables are keyed by "Participant_ID" (Condition + GUID) to allow for easy joining of tables.

We have removed NeuroLINCS data and the "Analyze" tab that previously used this data.

Users are now alerted to the size of data within the download script.

All sample data follows new naming and organization conventions as outlined in this example diagram.

Sex Effects in RNA-Seq data:

  • The standard step after obtaining level 3 data (Counts) is statistical inference of systematic changes between conditions (e.g ALS and CTR) by modeling gene expression data with a binary variable with two levels (design ~condition, condition =0 for CTR, 1 for ALS). In the presence of confounding factors a more complex design (e.g. design~batch + condition) may be needed to exact the disease relevant signal while controlling for the confounders.
  • In this data release, one of the dominating contributors to the gene expression changes observed in our initial principal component (PCA) analysis is the inherent sex effect. Genes that contribute to the sex effect include both sex chromosome linked genes and autosomal genes. This gender specific gene expression has also been reported in post mortem human brains, as well as IPSCs. In order to extract disease relevant signal, we recommend controlling sex effect for your downstream analysis. For example, excluding chrX, chrY linked genes and adding an additional binary variable to the design account for sex effect.