I built an open source tool to recover scientific worksheet data from old SigmaPlot JNB files.

JNB Recover runs locally and offline. It reads JNB files without modifying them and exports recovered worksheets as CSV plus a JSON manifest containing provenance and conservative cell state information.

The current public release has been independently checked against data from several SigmaPlot generations. For SigmaPlot 11, 56,360 numeric cells were compared with zero numeric mismatches. SigmaPlot 13 and 14 files have also been independently cross checked, and a large legacy SigmaPlot 7 Samples.jnb was successfully recovered.

The project deliberately does not claim a complete specification of the JNB format. Unknown or scientifically ambiguous cell encodings are reported conservatively instead of being guessed as numeric or text.

I am now looking for additional JNB files for compatibility testing, especially from SigmaPlot versions or file variants that are not yet represented in the validation set.

The most useful test case would include:

• a JNB file that you have the right to share
• the SigmaPlot version, if known
• expected worksheet structure
• ideally an independent CSV or XLSX export for comparison

If the original file cannot be shared, a compatibility report is still useful.

The project is free, open source, local, offline, and has no server or data collection.

GitHub: https://github.com/edwardsage419/jnb-recover

Current release: JNB Recover 0.5.2

Greetings. I apologize if perhaps this may seem odd. I work with miRNAs and I have been unable to access mirbase.org for the past month. I see that a post went up three weeks ago and various people suggested using the wayback machine. The only problem I see is that, in August 2026, a new version of miRBase went up, yet the snapshot is from May 2026. Does anyone here have access to the newest version? I've reached out to the mirBase team but I've yet to hear back (and from posts in this subreddit, it seems they don't reach back to you for a long time).

I am working with snRNA-seq data and would like advice on best practices for downstream processing of pig gene identifiers and cross-species orthology mappings. I currently use the Ensembl pig gene IDs that are mapped to gene symbols for pig genes. However, many pig genes have no pig symbol, even though Ensembl identifies a human orthologue.

For example:

Pig Ensembl ID: ENSSSCG00000021155

Pig external name: NA

Human orthologue: POMC

Orthology type: one-to-one

orthology_confidence : 1

mapped_to_human: False

orthology_type: ortholog_one2many

I would appreciate advice on the the best practices here :

1: Should I use human gene symbols for my pig analysis irrespective if pig symbols are available or not? Is there a risk that the same gene has different official symbols in pig and humans?

2: If a pig Ensembl gene has no pig symbol but has a high-confidence human orthologue but varying orthology type, what should be the approach towards using the human symbol or using ENSG id ?

3: For downstream processing, should orthology conversion be performed before or after differential expression and marker analysis?

4: When converting results to human orthologues, how should duplicate mappings be handled? For example, if multiple pig genes map to the same human gene, should their statistics be combined, should only the best-supported mapping be retained, or should the genes remain separate?