TALgetter

TALgetter allows you to scan input sequences for putative target sites of a given TAL (transcription activator like) effector as typically expressed by many Xanthomonas bacteria. TALgetter uses a local mixture model, which assumes that the nucleotide at each position of a putative target site may either be determined by the binding specificity of the RVD at that position (if binding occurs at that position) or by the genomic context (if no binding occurs). Binding specificities and importance of the individual RVDs has been trained on known TAL effector - target site pairs. Nucleotide preferences of the genomic context are learned from (putative) promoter sequences of A. thaliana and O. sativa.

Web-application

TALgetter is available as a web-application at galaxy.informatik.uni-halle.de:8976. Here, you can also download a command line application that is easily scriptable.

Download

TALgetter is implemented in Java using Jstacs. Here, can download the Jar of the command line application. In addition, we provide the Jar of the Galaxy web-application for installing it in your local Galaxy server.

Running the command line application

For running the command line application, Java v1.6 or later is required.

The arguments of the command line application have the following meaning:

name	comment	type
input	Input sequences (The sequences to scan for TAL binding sites, FastA)	String
tal	TAL sequence (Sequence of RVDs, seperated by '-', default = NI-HD-HD-NG-NN-NK-NK)	String
fp	First position (First position (counted from 5' end) considered for search, default = 0)	Integer
do	Downstream offset (Number of positions counted from 3' end that are not considered, default = 0)	Integer
top	Top N (Limit the number of reported hits in all input sequences to at most N, valid range = [1, 10000], default = 100)	Integer
pval	PVals (Computation of p-Values, range={NONE, COARSE, FINE}, default = COARSE)	{NONE, COARSE, FINE}
pthresh	p-Value (Filter the reported hits by a maximum p-Value. A value of 0 or 1 switches off the filter., valid range = [0.0, 1.0], default = 1.0)	Double
model	Model type (TALgetter is the default model that uses individual binding specificities for each RVD. TALgetter13 uses binding specificities that only depend on amino acid 13, i.e., the second amino acid of the repat.While TALgetter is recommended in most cases, the use of TALgetter13 may be beneficial if you search for target sites of TAL effector with many rare RVDs, for instance YG, HH, or S*., range={TALgetter, TALgetter13}, default = TALgetter)	{TALgetter, TALgetter13}
train	Training sequences (The sequence to use for training the model, annotated FastA, OPTIONAL)	String

If, for instance, you want to scan the FastA-file path/to/myPromoters.fa for the top 100 target sites of the TAL effector Talc, you start TALgetter with

java -jar TALgetter.jar input=path/to/myPromoters.fa tal="NS-NG-NS-HD-NI-NG-NN-NG-HD-NI-NN-N*-NI-NN-HD-NG-NI-NN-N*-HD-NN-NG"

Optionally, you can also train the TALgetter model using your custom training data. Here, we provide an example file of input sequence. Basically, the input format is an annotated FastA-File of the form

>seq:<RVD-sequence>; weight: <w>
<DNA-sequence including position 0>
...

for instance:

>seq:NI-NG-NN-NN-NI-HD-HD-NN-NG-NN-NG-; weight:0.0476190476190476
TATGGACCGTGT

The specification of the weight is optional.