SCnorm protocols

View SCnorm computational protocol

SCnorm statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.

Subscribe
info

Citations per year

Citations chart
info

Popular tool citations

chevron_left Normalization chevron_right
Popular tools chart
info

Tool usage distribution map

Tool usage distribution map
info

Associated diseases

Associated diseases

SCnorm specifications

Information


Unique identifier OMICS_13863
Name SCnorm
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input format UTF-8
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 2.0
Computer skills Advanced
Version 1.1.1
Stability Stable
Source code URL https://codeload.github.com/rhondabacher/SCnorm/tar.gz/v1.1.1
Maintained Yes

Download


Versioning


Add your version

Documentation


Maintainers


  • person_outline Christina Kendziorski <>
  • person_outline Rhonda Bacher <>

Publication for SCnorm

SCnorm in pipeline

2017
PMCID: 5746276
PMID: 29240790
DOI: 10.1371/journal.pbio.2004050

[…] them as missing. the wavecrest algorithm was also used as above to obtain a cyclic order on the set of unstressed single cells based on five rp genes ()., length-normalized read counts were taken as scnorm-normalized read counts per transcript divided by transcript length, and the mean (or median) for each transcript across all unstressed or stressed cells was calculated; mean and median values […]


To access a full list of citations, you will need to upgrade to our premium service.

SCnorm in publications

 (3)
PMCID: 5746276
PMID: 29240790
DOI: 10.1371/journal.pbio.2004050

[…] 1.5.0. sequenced wells were removed from the analysis if they had <1,000 total mapped reads or if the proportion of ercc spike-ins to total-mapped reads was > 0.2 []. data were normalized by scnorm [] in r version 3.3.1; ercc spike-in samples were not used in the normalization. normalized read counts for each gene were logged and then centered by subtracting the mean log2(read counts) […]

PMCID: 5815497
PMID: 28953884
DOI: 10.1038/nature24033

[…] was applied to the matrix, ensuring >50,000 total transcript reads per cell and >5 reads in at least 5 samples. the raw transcript counts were corrected for read-count depth effects using the scnorm package with a single-group design matrix. the ruvseq (version 1.10.0) was used for between-sample normalization by applying the ‘betweenlanenormalization’ function with ‘full’ quantile […]

PMCID: 1622760
PMID: 17042958
DOI: 10.1186/1471-2105-7-456

[…] label. we then go down the list and find the next structure that has a different label from c1. let us call this entry n2, and let c2 denote the label for n2 . next, we compute the scores, scnorm(q, n1) and scnorm(q, n2)., then we use these scores to compute f1 and f2 as: f1 = scnorm(q, n1) and f2 = scnorm(q, n1)/scnorm(q, n2). finally, we return the values f1, f2 and c1., intuitively, […]


To access a full list of publications, you will need to upgrade to our premium service.

SCnorm institution(s)
Department of Statistics, University of Wisconsin, Madison, WI, USA; Morgridge Institute for Research, Madison, WI, USA; Laboratory of Genetics, University of Wisconsin, Madison, WI, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA
SCnorm funding source(s)
Supported by NIH GM102756, NIH U54 AI117924, 1T32LM012413-01A1, NIH 5U01HL099773 and the Morgridge Institute for Research.

SCnorm reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review SCnorm