15 research outputs found
Approximate Profile Maximum Likelihood
We propose an efficient algorithm for approximate computation of the profile
maximum likelihood (PML), a variant of maximum likelihood maximizing the
probability of observing a sufficient statistic rather than the empirical
sample. The PML has appealing theoretical properties, but is difficult to
compute exactly. Inspired by observations gleaned from exactly solvable cases,
we look for an approximate PML solution, which, intuitively, clumps comparably
frequent symbols into one symbol. This amounts to lower-bounding a certain
matrix permanent by summing over a subgroup of the symmetric group rather than
the whole group during the computation. We extensively experiment with the
approximate solution, and find the empirical performance of our approach is
competitive and sometimes significantly better than state-of-the-art
performance for various estimation problems
Additional file 4: Table S2. of Circulating tumor cells (CTC) and KRAS mutant circulating free DNA (cfDNA) detection in peripheral blood as biomarkers in patients diagnosed with exocrine pancreatic cancer
Statistical analysis of overall survival with regard to the detection of CTC and mutant KRAS cfDNA in plasma. N.B: The Cox and Weibull regression are corrected by age and sex. (DOC 30 kb
Additional file 5: Figure S3. of Circulating tumor cells (CTC) and KRAS mutant circulating free DNA (cfDNA) detection in peripheral blood as biomarkers in patients diagnosed with exocrine pancreatic cancer
Estimated Survival Curves adjusted by sex and age using Cox regression for CTC and KRAS Mutant models. (PDF 23 kb
Additional file 13 of Differential distribution and enrichment of non-coding RNAs in exosomes from normal and Cancer-associated fibroblasts in colorectal cancer
: Multiple alignment of the 42 sncRNAs over represented in CAF-EXO samples. (FASTA 8 kb
Additional file 2: of Differential distribution and enrichment of non-coding RNAs in exosomes from normal and Cancer-associated fibroblasts in colorectal cancer
Absolute and average relative counts of reads mapped to each ncRNAs biotype per sample and fraction. (XLSX 15 kb
Additional file 4: of Differential distribution and enrichment of non-coding RNAs in exosomes from normal and Cancer-associated fibroblasts in colorectal cancer
Figure S1. logFC-based MDS-plots (one for each type of lncRNA), where the first dimension corresponds to differences due to the type of sample (i.e. whether it is a normal cell, a tumor cell or an exosomal sample) and the second dimension corresponds to the differences between the samples themselves as biological replicates. The inferred dispersion and the Biological Coefficient of Variation (BCV) of all assayed samples for lncRNAs are 0.21201 and 0.4604, respectively, while the coefficients for sncRNA content are 0.25164 and 0.5016. These two coefficients reveal some interesting variation among samples. In this respect the multidimensional scaling (MDS) plots where the differences in ncRNA content between cellular and exosomal fractions and the heterogeneity of CAF samples, and especially their exosomes, are indicated as the main cause of this variation. Moreover, since each sequenced sample was prepared as a pool of three others and CAF samples and their exosomes are, as expected, more heterogenous because of their tumoral condition, then their variability should also be greater than that of NFs and their exosomes. Figure S1 also gives some differences that exist between NF and CAF exosomes. (PNG 104 kb
Additional file 5: of Differential distribution and enrichment of non-coding RNAs in exosomes from normal and Cancer-associated fibroblasts in colorectal cancer
Excel file with two documents summarizing the results obtained from the differential expression NF-CELL versus NF-EXO analyses for differentially distributed lncRNAs and sncRNAs. (XLSX 73 kb
Additional file 7: of Differential distribution and enrichment of non-coding RNAs in exosomes from normal and Cancer-associated fibroblasts in colorectal cancer
Mini web site presenting a dynamic venn diagram intersecting the relationships of significance from the assayed ncRNAs in the differential expression analyses performed between NF- and CAF- exosomes versus their respective cellular environments (i.e. NF-CELL versus NF-EXO and CAF-CELL versus CAF-EXO). Clicking on any intersected number, the web site opens a dialog summarizing the ncRNAs species that correspond to the intersection. (HTML 120 kb
Additional file 11: of Differential distribution and enrichment of non-coding RNAs in exosomes from normal and Cancer-associated fibroblasts in colorectal cancer
Table S1. sncRNAs distributed differently in CAF-EXO samples from in NF-EXO ones. Highly significant lncRNAs and sncRNAs (FDR < 1E-04) are highlighted in bold. (DOCX 79 kb