Name | Modified | Size | Downloads / Week |
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R package | 2022-07-19 | ||
README.txt | 2022-07-19 | 2.1 kB | |
dataMAPPs_3.4.1.zip | 2021-03-18 | 19.8 MB | |
dataMAPPs_3.2.7.zip | 2020-05-25 | 22.5 MB | |
Totals: 4 Items | 42.3 MB | 0 |
Release 3.6.0, Jul 19, 2022 - dataMAPPs is now available as an R package! (see content in "R package" folder) To install, download the packages lemur and dataMAPPs and install in that order using install.packages(<path to .tar.gz file>, repos=NULL) - Documentation is still at its beginning, but have a look at the two vignettes for 1. processing of the included example data and 2. general package configuration - dataMAPPs core version 3.6.0 features lots of little improvements and fixes, as well as new function calls that allow modularization of the workflow, thus easier integration in another lab environment. (See vignette example for separating the steps of sample list & data import, MAPPs object generation and running through the processing steps with just one function call.) Release 3.4.1, Mar 18, 2021 - Added a template for the minimal typical processing of a new dataset, hopefully helping a great deal to get started - added a template for the PSM format that is now usable with dataMAPPs Release 3.4.0, Mar 17, 2021 - PSM files can be imported, and by specifying format = "ANY" in read_MAPPs_data() any suitable file is imported and merged, whether original PEAKS or PSM or PROGENSIS format - removed dependency on reshape2, using tidyr pivoting functions consistently - using cowplot to create multiple plot layouts - replaced deprecated dplyr::combine everywhere in the code - lots of small fixes and code cleanup, improving overall stability Release 3.2.7, May 25, 2020 - pseudo domains (see update 3.2.5) are now ordered by position in sequence - added package identifiers for dplyr::select() calls in example processing file in order to prevent an abort due to calling a wrong function - minor adjustment of metadata files Release 3.2.5, Apr 28, 2020 - some minor internal fixes to increase stability of data loading - forms 'pseudo domains' for unassigned sequence stretches in case a domain structure for a target protein is provided by the user and not the whole sequence is covered by those domains. Threw an error previously.