Journal article
MALTA: a calculator for estimating the coverage with shRNA, CRISPR, and cDNA libraries
SoftwareX, Vol.9, pp.154-160
01/01/2019
DOI: 10.1016/j.softx.2019.01.006
PMCID: PMC6625779
PMID: 31304228
Abstract
Genetic screens using shRNA, CRISPR, or cDNA libraries rely on adequately transferring the library into cells for further assay. These libraries can have many different elements and each element can be present at different copy numbers within a given pooled library. Calculating how many recipient cells are needed to adequately sample all or most of the different elements within a library is important, especially if one wants to compare the outcomes of different genetic screens that rely on accurately reproducing the starting population of library-containing cells. Here we present a simple application that starts with a list of library elements and their abundance and calculates the minimum sampling number to achieve full transfer of the library to an acceptor cell population to a user-specified level of probability. Users can adjust several input parameters including designating a subpopulation over which the calculation is made. Finally, the program performs a series of Monte Carlo simulations of a user-specified number of picks to produce an empirically determined distribution of each library element.
Details
- Title: Subtitle
- MALTA: a calculator for estimating the coverage with shRNA, CRISPR, and cDNA libraries
- Creators
- Venkatramanan Krishnamani - University of IowaMark A. Stamnes - University of IowaRobert C. Piper - University of Iowa
- Resource Type
- Journal article
- Publication Details
- SoftwareX, Vol.9, pp.154-160
- DOI
- 10.1016/j.softx.2019.01.006
- PMID
- 31304228
- PMCID
- PMC6625779
- NLM abbreviation
- SoftwareX
- ISSN
- 2352-7110
- eISSN
- 2352-7110
- Grant note
- DOI: 10.13039/100000002, name: NIH, USA, award: RO1 GM58202, R21 EB021870-01A1; DOI: 10.13039/100000001, name: NSF, USA, award: 1517110
- Language
- English
- Date published
- 01/01/2019
- Academic Unit
- Molecular Physiology and Biophysics; Medicine Administration; Internal Medicine
- Record Identifier
- 9984297600002771
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