---
id: "claim:long-read-sequencing-transcriptome-quantification-with-lr-kallisto-2025-12-01-p-c105976de1:a45b2f73c885e2eb9568"
kind: "claim"
title: "lr-kallisto can analyze older published long-read datasets."
description: ""
url: "https://sina.bio/claim/lr-kallisto-can-analyze-older-published-long-read-datasets"
---

# lr-kallisto can analyze older published long-read datasets.

## Content

lr-kallisto can analyze older published long-read datasets.

## Metadata

```json
{
  "claim_position": 41,
  "source_publication_id": "version:long-read-sequencing-transcriptome-quantification-with-lr-kallisto--2025-12-01-plos-computational-biology",
  "source_work_id": "work:long-read-sequencing-transcriptome-quantification-with-lr-kallisto"
}
```

## Connections (1)

### Long-read sequencing transcriptome quantification with lr-kallisto

- ID: `version:long-read-sequencing-transcriptome-quantification-with-lr-kallisto--2025-12-01-plos-computational-biology`
- Kind: `publication`
- Direction: `incoming`
- URL: <https://sina.bio/publication/long-read-sequencing-transcriptome-quantification-with-lr-kallisto-3ccc217c>

This publication contains this grounded claim.

> Furthermore, we show that lr-kallisto is robust to error rates, making it suit- able also for the analysis of previously published older long-read sequencing data.

Source: 2025-12-01-plos-computational-biology.pdf — <https://sina.bio/source/2025-12-01-plos-computational-biology-pdf>