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1.
Fig. 4

Fig. 4. From: BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes.

ASB detection from FAIRE targeted sequencing data. a Correlations between the allelic ratios obtained from gDNA and FAIRE-seq data. b Density plots showing the distribution of allelic ratios before (green) and after (orange) BaalChIP correction. The adjusted AR values were estimated by the BaalChIP model after taking into account the RAF scores computed directly from the control gDNA samples. AR allelic ratio, ASB allelic-specific binding, cor correlation, gDNA genomic DNA, RAF reference-allele frequency

Ines de Santiago, et al. Genome Biol. 2017;18:39.
2.
Fig. 2

Fig. 2. From: BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes.

The ROC curve comparison between BaalChIP and other allele-specific SNP finding methods: binomial test and iASeq, using a simulated data set. The BaalChIP result is shown by solid red line. Binomial test and iASeq are shown in dashed blue and black lines. The number of TFs able to bind at a given SNP and the number of reads per TF increases from TF = 3, Reads per TF = 1 (a, b, c) to TF = 5, Reads per TF = 8 (d, e, f) to TF = 15, Reads per TF = 15 (g, h, i). RAF is decreasing from 0.5 (a, d, g) to 0.3 (b, e, g) to 0.1 (c, f, i)

Ines de Santiago, et al. Genome Biol. 2017;18:39.
3.
Fig. 3

Fig. 3. From: BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes.

Examples of cancer and non-cancer cell lines from SNP and ChIP-seq ENCODE data. a B allele frequencies (BAFs) for chromosome 1 for three cancer cell lines (MCF-7, K562, and SK-N-SH) and one non-cancer cell line (GM12878). Individual SNPs are colored according to genotype values: homozygous AA or BB (blue) and heterozygous AB (orange). b Correlations between the BAF values and the ChIP-seq AR of heterozygous SNPs. RAF corresponds to the BAF value with respect to the reference allele (RAF is equal to BAF if the reference allele corresponds to the B allele; RAF is equal to 1 − BAF if the reference allele corresponds to the A allele). The fitted linear model (blue line) and the Spearman correlation coefficient (cor) show the relationship between BAF and ChIP-seq ARs at heterozygous sites. AR allelic ratio, BAF B allele frequency, chr1 chromosome 1, cor correlation, RAF reference-allele frequency, SNP single-nucleotide polymorphism

Ines de Santiago, et al. Genome Biol. 2017;18:39.
4.
Fig. 5

Fig. 5. From: BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes.

Comparison of BaalChIP with other available methods. Left y-axis corresponds to the frequency of ASB events called by BaalChIP or the binomial tests (red, blue and purple lines). Right y-axis corresponds to the mean of the posterior probability given by the iASeq method (black line). The numbers at the top of the plot show the total number of tested heterozygous sites in each bin. a SNPs were grouped in bins of different RAF intervals. The RAF intervals increase in terms of distance to the diploid value (RAF = 0.5). The binomial test (without RAF correction; purple line) and the iASeq methods (black line) are biased towards the detection of ASB events in regions of altered copy numbers. b SNPs were grouped in bins of different depth of coverage. SNPs in regions RAF < 0.4 or RAF > 0.6 were excluded from this analysis. When applying the binomial test (purple and blue lines), the frequency of ASB detection increases for higher covered sites, while the same is not true when applying BaalChIP or the iASeq methods. The effect is particularly visible for the FAIRE-seq data set. ASB allelic-specific binding, binom binomial, RAF reference-allele frequency, SNP single-nucleotide polymorphism

Ines de Santiago, et al. Genome Biol. 2017;18:39.
5.
Fig. 1

Fig. 1. From: BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes.

Description of BaalChIP model. a The basic inputs for Baal are the ChIP-seq raw read counts in a standard BAM alignment format, a BED file with the genomic regions of interest (such as ChIP-seq peaks), and a set of heterozygous SNPs in a tab-delimited text file. Optionally, genomic DNA BAM files can be specified for RAF computation. Alternatively, the user can specify the pre-computed RAF scores for each variant. b The first module of BaalChIP consists of (1) computing allelic read counts for each heterozygous SNP in peak regions and (2) a round of filters to exclude heterozygous SNPs that are susceptible to generating artifactual ASB effects. (3) The reference mapping (RM) bias and the reference-allele frequency (RAF) are computed internally and the output consists of a data matrix where RM and RAF scores are included alongside information about allele counts for each heterozygous SNP. The column Peak contains binary data to indicate the called peaks. c The second module of BaalChIP consists of calling ASB binding events. (4) BaalChIP uses a beta-binomial Bayesian model to consider RM and RAF bias when detecting ASB events. d The output from BaalChIP is a posterior distribution for each SNP. A threshold to identify SNPs with allelic bias is specified by the user (default value is a 95% interval). (5) The output of BaalChIP is a credible interval (lower and upper) calculated based on the posterior distribution. This interval corresponds to the true AR in read counts (i.e., after correcting for RM and RAF biases). An ASB event is called if the lower and upper limits of the interval are outside the 0.4–0.6 interval. Alt alternative, AR allelic ratio, ASB allelic-specific binding, gDNA genomic DNA, Het. heterozygous, MAPQ, mapping quality, NA not applicable, RAF reference-allele frequency, Ref reference, Rep repeat, RM reference mapping, SNP single-nucleotide polymorphism, TF transcription factor

Ines de Santiago, et al. Genome Biol. 2017;18:39.

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