Return to study ST002983 main page
MB Sample ID: SA323713
| Local Sample ID: | HSCb_14 |
| Subject ID: | SU003096 |
| Subject Type: | Mammal |
| Subject Species: | Mus musculus |
| Taxonomy ID: | 10090 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN004902 |
|---|---|
| Analysis type | MS |
| Chromatography type | None (Direct infusion) |
| Chromatography system | none |
| Column | none |
| MS Type | MALDI |
| MS instrument type | MALDI-TOF-MS |
| MS instrument name | Bruker Autoflex MALDI-TOF (/TOF)-MS |
| Ion Mode | POSITIVE |
| Units | intensity |
MS:
| MS ID: | MS004645 |
| Analysis ID: | AN004902 |
| Instrument Name: | Bruker Autoflex MALDI-TOF (/TOF)-MS |
| Instrument Type: | MALDI-TOF-MS |
| MS Type: | MALDI |
| MS Comments: | MS acquisition Comments: MS experiments were conducted on the Autoflex MALDI-TOF (/TOF)-MS (Bruker Autoflex Speed) with Nd:YAG lasers (355 nm) and smart beam system. All MS experiments were performed in the reflector positive ion mode, with 2000 laser shots per analysis and 5 independent experiments per sample. Data processing Comments:MS data preprocessing was carried out on python version 3.8, including peak detection, peak filtration, standardization, and batch effect removal by ComBat algorithm. The heatmap, hierarchical clustering analysis, Pearson correlation analysis and PCA analysis were performed on MetaboAnalyst 5.0 (https://www.metaboanalyst.ca/). Machine learning and t-SNE clustering were conducted on Orange (version 3.25.0, the Bioinformatics Lab at University of Ljubljana, Slovenia). Software/procedures used for feature assignments: Python |
| Ion Mode: | POSITIVE |
