Additional file 1 of A novel scan statistics approach for clustering identification and comparison in binary genomic data

Table S1. Full list of HIV clusters. (PDF 49 kb

Additional file 4 of A novel scan statistics approach for clustering identification and comparison in binary genomic data

Figure S1. Relative scan statistics results for remaining chromosomes. (PDF 5089 kb

Comparison with Arnvig, et al. [10] annotated sRNA.

<p>Comparison with Arnvig, et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032723#pone.0032723-Arnvig1" target="_blank">[10]</a> annotated sRNA.</p

Complete list of weights <i>w_j</i> for conservation map calculation.

<p>For each genome of the comparison set the corresponding Ref Seq accession number and the evolutionary distance from MTB genome are reported. The sum of <i>w_j</i> is equal to 6.22 that correspond to the upper limit of conservation value <i>C_i</i>.</p

Candidate classification based on candidate definition provided in 2.4.

<p>Candidate classification based on candidate definition provided in 2.4.</p

Comparison with DiChiara, et al. [11] sRNAs annotated in <i>Mycobacterium bovis</i> BCG.

<p>Comparison with DiChiara, et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032723#pone.0032723-DiChiara1" target="_blank">[11]</a> sRNAs annotated in <i>Mycobacterium bovis</i> BCG.</p

Outline of the bioinformatic pipeline.

<p>(a) Construction of the effective target genome (ETG) in terms both of sequences and coordinates. (b) Construction of the two strand specific reads maps. (c) Construction of two strand specific conservation maps. (d) Combination of reads and conservation map to allow for the identification of putative sRNA encoding regions. (e) annotations of putative sRNA to assess their reliability.</p

Reads maps construction.

<p>Reads map (blue curve) is obtained by assembling together all reads (sequences in red) mapping uniquely and completely within the same IGR or AS region (sequence in black). The BioPerl procedure implemented merges NGS mappers output and T_IGRAScoord files.</p

SRNA identification process.

<p>For each IGR (sequence in black), reads (blue curve) and conservation (green curve) maps are superimposed. First Type A candidates (highlighted in blue) are identified and extracted by testing length constrains (conditions I and II) and reads coverage above ExprT1 (dotted blue line). On the remaining portions of IGRs, Type B candidates (highlight in yellow) are identified and extracted by testing length constrains (conditions I and II) and contemporaneously both reads coverage above ExprT2 and conservation depth above ConsT2 (dot and dashed yellow lines). Finally, Type C candidate (highlighted in green) are identified in the remaining IGRs on the basis of high sequence conservation (above ConsT1 threshold reported as dotted green line).</p

Genomic distribution and association with histone modifications of MLV and SIN-MLV integrations in human HSPCs.

<p>Distribution of the distance of SIN-MLV (green bars) and MLV (red bars) integration sites from the TSS of targeted genes at 2,500 bp (<b>a</b>) or 50 bp (<b>b</b>) resolution. The percentage of genes targeted at each position is plotted on the y axis. The number of plotted sites is higher than the actual number of mapped integrations sites, since each site may relate to more than one gene. The black line indicates the distribution of random control sites. (<b>c</b>) The distribution of H3K4me1 (top panels) and H3K4me3 (lower panels) epigenetic marks in a 10-kb window around vector integration sites (IS) is shown for MLV integrations (left panels) or SIN-MLV integrations (right panels). The mean density of tags (tag/50 bp) of the reference dataset (i.e. each chromatin feature) is plotted on the y axis. The scale of the graph is shown at the top left of each panel.</p