Name
Title | ||
|---|---|---|
RNASeq_similarity_matrix: visually identify sample mix-ups in RNASeq data using a 'genomic' sequence similarity matrix. |
Abstract | ||
|---|---|---|
A Summary: Mistakes in linking a patient's biological samples with their phenotype data can confound RNA-Seq studies. The current method for avoiding such sample mix-ups is to test for inconsistencies between biological data and known phenotype data such as sex. However, in DNA studies a common QC step is to check for unexpected relatedness between samples. Here, we extend this method to RNA-Seq, which allows the detection of duplicated samples without relying on identifying inconsistencies with phenotype data. Results: We present RNASeq_similarity_matrix: an automated tool to generate a sequence similarity matrix from RNA-Seq data, which can be used to visually identify sample mix-ups. This is particularly useful when a study contains multiple samples from the same individual, but can also detect contamination in studies with only one sample per individual. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1093/bioinformatics/btz821 | BIOINFORMATICS |
Field | DocType | Volume |
Data mining,Computer science,Computational biology,Similarity matrix | Journal | 36 |
Issue | ISSN | Citations |
6 | 1367-4803 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicolaas C Kist | 1 | 0 | 0.34 |
| Robert A Power | 2 | 0 | 0.34 |
| Andrew Skelton | 3 | 0 | 0.34 |
| Seth D Seegobin | 4 | 0 | 0.34 |
| Moira Verbelen | 5 | 0 | 0.34 |
| Bushan Bonde | 6 | 0 | 0.34 |
| Karim Malki | 7 | 1 | 1.07 |