not giving result for the pan-disease expression plot

[AnkitYGeneSeq]

I am currently using the CARE tool for my analysis, and while it runs smoothly with my sample data, I am encountering an issue when attempting to obtain results for the pan disease cohort. also, I updated the manifest.tsv file, but still it is not giving the pan disease cohort result

[hbeale]

What is the "disease" value you used in the manifest.tsv? Where are you looking for the pan disease cohort result?

[AnkitYGeneSeq]

I’m looking for the ovarian cancer so i used “ovarian serous
cystadenocarcinoma” in the manifest.tsv file but it is generating only for the pan cancer expression plot

[hbeale]

Thanks. Can you send me the Summary.html at hcbeale@ucsc.edu?

[hbeale]

Thank you for sending the pdf of Summary.html. I think the root problem is that the RNA-Seq data does not contain enough informative reads, so meaningful comparisons cannot be made with our compendium. We measure Mapped, Exonic, Non-duplicate (MEND) reads. On the first page of Summary.html, you can see that the sample failed MEND QC, having 0.7 million MEND reads while we require 10 million to pass QC. The sample has less than 10% of the data required. While your data has plenty of total reads (17 million), 81% are duplicates (page 25, "Metrics"). MEND reads are described here.

(I am assuming that you ran the Treehouse alignment, quantification and qc Pipelines as described here.)

Although the analysis reported no pan-disease outliers, I recommend that you also be skeptical of the pan-cancer outlier results. I believe too few genes were measured due to the lack of informative reads. The low number of measured genes causes each gene's allotment of TPM (which I think of as slices of a pie: fewer slices = bigger slices) to be larger than in most samples. In the Metrics section, you can see that 19.73 thousand genes were measured in your sample, while the typical range is 24.76 - 29.7. The analysis returned 606 pan cancer up-outliers, while the typical range is 97.04 - 285.05. Together with the low MEND read count, these indicate that the pan-cancer results are a result of technical variation, not biological variation.

The specific reason you got no pan-disease outliers is that only one of the four personalized cohorts has any members. For example, in the "Diagnosis Composition of Personalized Cohorts" section, one row contains "First-Degree MCS" in the left column, and "Total —0 (Below minimum size; does not contribute to outlier analysis)" in the right column.

CARE uses consensus based identification of pan-disease outliers, requiring that the gene is an outlier relative to at least 2 cohorts. That is why CARE reports no pan-disease results for your sample.

The three cohorts with no samples are all based on correlation. Looking at "Most Correlated Samples with Clinical info", the highest correlation is 0.35. That is an exceptionally low correlation. We usually consider correlation scores in the top 5% of all correlation scores among all samples; the threshold for the top 5% for the v10 polyA compendium is 0.874. This is another indication that the RNA-Seq data for your sample is not comparable to the compendium.

I'm sorry for the bad news. Please reach out if there's another way we can help you use CARE.